Welcome to WISIS Forum 2022 here in Geneva and with me is His Excellency Mohamed Al-Qaedaid. Mohamed Al-Qaedaid, you are Chief Executive Information E-Government Authority of Bahrain. And congratulations because you've been nominated as one of the champion projects. Can you tell me about that project? Yeah, thank you very much. The project, of course, is about the digital policies. As you know, lots of achievements happened in terms of infrastructure, accessibility. Mobile penetration is very high, Bahrain ranks first in the Middle East in terms of the infrastructure readiness. The people adoption is, you know, they're adapting to the services. And we have a lot of online services as well as many enablers. But when it comes to government entities, still there were some government entities providing their services in a traditional way. So the cabinet took the decision that we should issue policies that force everybody to follow called digital policies. One of them is digital right, you know, the right to digital government, where we try to enable and make sure that, you know, legislations are there. People are get the knowledge to use the technologies as well that the government and their infrastructure are ready to provide the government services properly with, you know, with the with the cloud and other things to be to be supporting to it. That's one. The other one is the digital first. Any entity would like to introduce their service, which they should go electronic first, instead of, you know, giving it traditionally and then facing the challenges or, you know, the people or maybe government employees, they should provide it electronically and then if needed, for some people who disadvantage or cannot access, then they can provide it otherwise. You mentioned there briefly populations that aren't yet connected and we know that that is an issue. What are the challenges in that respect of meeting sustainable development goals, particularly around equitable access to information technologies? I think maybe in Bahrain, we don't have that kind of challenge because, you know, the penetration is almost 100%. Really? We have like 98% of penetration elder people being, you know, we don't have disadvantage. We have most of the people are using, but sometimes it's just people prefer and, you know, as as an enabler or working in this field for a very long time, sometimes you cannot blame the people not using the electronic service because maybe the electronic service is not very efficient, or maybe it requires going from ministry to other one, or maybe requiring it's a bit complicated. So this is why, you know, the policies came to complement. So it's not about disadvantage that they don't have access or they don't know how to use it. Maybe it's taking more steps or time than the traditional one. So this is why we wanted to drift from the physical to the electronic service. But there are other challenges like, you know, the technologies evolve and the changes every day, you know, blockchain, cloud, whatever. And if you don't do it right, and you have to reinvest. And that's a duplication. Not all countries can. And has an environmental impact every time you repeat doing something. Exactly. And you know, you have reinvest and you have to redo it and you're already invested, maybe you don't have that kind of luxury to, you know, to spend more money to doing that. Sometimes you don't have the priority, okay, there are 10 technologies, which one I have to stick to, which one to. And here I think it's the importance of maybe the UN or other international agencies to help those countries, okay, categorize them. Okay, the least develop that they fall under this kind of category. They should use those technologies because more beneficial to them. And you know, I think that kind of maybe challenge can be overcome by having a more like geographical areas, like what we're doing in the GCC, for example. We have a committee, executive committee that we meet every twice a year. We have a strategy. We have initiatives that we work together, exchange of experiences, because our challenges are similar, our opportunities are similar, so we can help each other. And that actually was complimented by the UN and the report of the UN index as one of the initiatives that helped the six countries to become in the top Asian countries. And if we repeat this in Africa, North Africa, South Africa, or countries similar to each other, with maybe somebody having the insight of being a consultant, the UN, or helping or developing a kind of strategies that aligned according to the geographical area, I think that would help very much. It's been fascinating speaking with you. Thank you so much for your excellent team.


I'm Hayden Fulham, call sign gator. We're at Republic Airfield at the American Air Power Museum in Farmingdale, New York. This was the home of Republic Aviation and eventually Fairchild Republic who built our airplane. So the hangar we're in right now was the final assembly building for all the P-47s. The F-105 Thunder Chief and they use this building as well for the assembly of the A-10s. The F-105s inspire the paint scheme that we currently have on our demo jets. That woodland camouflage that we commemorate on Tail 962 on our A-10 for the demonstration. There's been a lot more excitement for the A-10 than I even expected to come back here. A lot of the folks we have met that volunteer or work here at the museum or still here at the airfield either worked for Fairchild Republic, had family who did, their mom, their dad, their uncle. They remember seeing the airplanes out on the flight line. It's been pretty impressive how many folks have stories to share seeing our A-10s back at Republic Airfield.


Hi, my name is Alisa and my favorite scripture from the Book of Mormon changes from time to time just depending on what phase of my life I'm in and what's going on and right now we have five kids that range in age from one to nine and so life is very busy and very full and Just because of the ages of my kids, you know, they're also pretty young and And so a lot of is required of me physically spiritually mentally emotionally just everything a lot is required a lot of time and There's a scripture in Alma 26 12 That says that in his strength I can do all things and actually there's a similar scripture in the Bible in Philippians 413 that says I can do all things through Christ which strengtheneth me and I love these scriptures because they bring me peace and comfort because I know that I can trust in the Lord and that he will He will strengthen me and that he will always be there for me and I can count on him to help me accomplish all the things that I need to do and And yeah, that's all so I say these things in the name of Jesus Christ amen


Kentucky Blood Center is now testing blood donors for COVID-19 antibodies. Now through October 3rd, blood donated at blood center locations will be tested to see if it contains the antibodies unless the donor opts out of the program. Seven to ten days after donating blood, donors can log on to their accounts online to find out their status. If they have the antibodies, they will then be asked if they wish to donate plasma to help in the fight against their coronavirus. So we are doing this free of charge to all donors in hopes that we can find donors that have tested positive for the antibody and we can hopefully get them to come back in our donor centers for a plasma donation so we can have that convalescent plasma for our COVID-19 patients. The convalescent plasma is used for patients that are in critical need or in a critical condition. The convalescent plasma helps that COVID-19 patient. The testing is being performed in addition to other incentives donors receive. Only blood collected at donor centers, not mobile units, is eligible for testing. Because of coronavirus restrictions, donors must schedule an appointment to donate. To find out more about the program or to register to donate, visit kybloodcenter.org.


Hello and welcome to the session. In this session we discussed the following question which says determine the slope and y-intercept of the following line y is equal to minus 2x plus 3. Before we move on to the solution, let's recall the slope-intercept form of a line. The slope-intercept form of a line is given by y is equal to mx plus c where we have this m is the slope of the straight line and c is the y-intercept of the straight line or you can say the coefficient of x that is m is the slope of the straight line and the constant term that is c would be the y-intercept of the straight line. This is the key idea that we use for this question. Let's proceed with the solution now. We are given the line y is equal to minus 2x plus 3. We need to find the slope and the y-intercept of this line. Now let this given equation of line be equation 1. Now next we compare this equation of line with the slope-intercept form of the line. So comparing the equation 1 with the slope intercept form of the line which is y is equal to mx plus c we find that this m is equal to minus 2 and c is equal to 3. So we say slope of the given equation of the line which is y is equal to minus 2x plus 3 is minus 2 and y-intercept of the given equation of line which is y is equal to minus 2x plus 3 is 3. So this is the final answer. This completes the session. Hope you have understood the solution of this question.


I'm at City Hall this morning because of the awareness and the importance of breast cancer awareness month. It is very important that not only do women and those of us and our sisters of course look at screening, look at education, to look at that whole gambit of things as it relates to breast cancer. As you know some years ago one out of seven, one out of seven women are crucially affected with breast cancer and of course I'm here today to not only to support our sisters but also to support this whole issue of education, screening, mammogram technology. Technology has grown in such a way these last few years that it is easily and readily detected. My wife was a breast cancer survivor until of course it came back. I'm here today because of my daughter and every other woman in the city of Columbia who has the wherewithal to look at the technological needs, the medical needs related to breast cancer. I would hope that not only do we recognize October as breast cancer month but we look at it 365 days a year because it is extremely important.


Everyone shiver 1,000 here today, we're going to be doing some time trials with the the Corvette challenge the Challenge 100 with the Corvette from taiko. This is the set we're going to be using used to be her dad's This track is in Near perfect condition While the track itself the cars and everything's fine There is a couple issues on some of the guard rails on two of the guard rails But other than that this thing is in perfect still in the original packaging and stuff so what we're going to do is there's a red red Corvette and a blue Corvette so There they are the red one used to be faster last time I had this out I oiled up the blue Corvette and it seems like it's faster But let's see what what we can let's see which one's actually faster with this Time thing here. I've got and it'll keep track of the laps and how much What the fastest lap was what the slow slap was and what the? the Average lap time is so let's get you set up so you can see better and We'll start running the cars Hey guys, so how this is going to work is? I'm on the wrong side of the screen. I Want to run them on the same track the same side of the track. I should say I'm going to use the same controller And I'm going to run as fast as I can without crashing if I crash we're going to start that over So I want us to be as fair as possible So but what we're going to do I haven't run these yet We're going to start with the red one. I've got everything punched in. I'm doing 20 laps We're going to do 20 warm-up laps on each car. So we're going to start with the red one and do 20 warm-up laps and We'll do the same thing with the blue one, but first let's go ahead and start this Okay, we're going to we'll start this over even though. It's just warm up We're going to start it over and get 20 20 Solid laps in what we're going to do my body actually came off the car that time so Let me see something here My glasses All right monkeys messaging me I may have to reset this all back up because every time I go and check something on here I have to reset this back up. So hang tight guys. Okay. Here we go. Let's try this again I do have it on full start So if I take off before the the gate lights are done, it'll it'll red flag me So let's start this 20 laps. It's like two laps is considered one lap for some reason I don't know if I got to set up the time on it or whatever Okay So it should tell us fastest slowest in average fastest lap 2.29 seconds slowest lap lap 20 2.94 seconds Shabare average lap time 2.67 seconds Okay, now let's try this For real And then we're going to do same thing with the blue one. We're going to run 20 laps. I'm going to keep track of what we got here so Let's go ahead and let's restart this You got to watch the shadows if it picks up shadows or any kind of movement It'll do that Countdown started Five seconds. That's the fastest I can go without creation We're not going I'm not trying to do driving skills here. I'm just trying to see which car Runs the the fastest average lap All right, let's stop this we're going to start it again Here we go. I'm almost getting there. Hang on. I gotta check my phone again Okay, guys. Here we go again. This is the real deal The car seems to be running pretty good. I'm going to have a live stream Friday the 22nd Of the christmas lights outside like we did last year Here we go Now I'm running this the fast I think I can without spinning out and there we are Let's hear what we got 2.78 seconds 2.78 Seconds. All right, there's a red one. There's our fastest lap or slowest and then our average So Let's see that was the fastest That was the slowest and that's average. All right, so we're going to do something up here Fastest Slowest and then the average ABG All right. Now let's put the blue one on. We're going to run 20 laps All right We're going to run 20 lap warm up laps. I like the car warm up and then we're going to Dive into the to the actual Time trial here. See it picked up my shadow They're releasing her mom today. So So it should be a little bit, but all right Here we go Five seconds This car is a lot faster Like I said, we'll do the 20 laps to warm it up and then you call these hot laps Like in real racing when you run some hot laps, you just kind of get used to the track checking your car out See if it needs any adjustment Yeah, I think this car is faster Now it wasn't before it used to be the red one And there we go That's already faster All right, here we go. This is the real work the real time here Or the real time trial Keep wanting to take off as soon as I hear that. All right, we gotta start over again Bring this around. Ah, come on I get one under two seconds, but it can't happen. I'm sure. All right. Let's see what we got here Shabair average lap time 2.84 seconds. Oh Okay, so right there it is Red one's still faster 2.78 average. So I'll tell you what I'm going to do. I'm going to all of these cars I'm going to write them 20 laps again Each and then we're going to do a time trial. So let me get that done and I'll be back with you Okay, so I got the blue car oiled up I ran in a few laps to get it warmed up now. Let's give it a shot our average on the blue car was 2.84 seconds. So let's see our fastest was 2.73 And our slows was 2.94. So Let's do this All right, here we go. Let's do this again I just qualified myself It's time you hear that little tune. That means it's the fastest lap So I was getting faster the first few laps. Okay This is after 2.52 2.93 seconds 9 3 was the slowest average lap time 2.67 seconds 2.67 seconds So that is faster than the red one at 2.78 since I oiled it the Before I oiled it it was uh 2.84 was average now, you know, some people Might be able to race this better like open it wide open on straights and then off on the corners I'm just going as fast as I can steadily So I'm going to oil the red one run into a couple laps and then we're going to check the lap time on it. Okay, so We're getting ready here reset. I ran 20 laps didn't really pay that much attention didn't write anything down Seems like it was a little quicker, but let's go ahead and start it now Sometimes we're sounding pretty good 2.44 That's because it crashed 2.67 seconds. Wow the same as the blue I don't what you guys are seeing there same as the blue car average so Um, this was because I crashed the slowest lap Wow That's pretty cool So they're pretty pretty even cars um The fastest lap on the blue one was uh 2.52 but on the red one. This is after oiling is a 2.44 so But then again the slowest one Was because I crashed over there. All right. I'm going to run these a few more times and then I'll be back with you Okay, so I just ran them both again The blue one ran a 2.61 which is faster than before and the red one ran a 2.56 So we're going to say the red one's still faster Um, I know there's a lot of variables here. This is not science, but it's a lot of fun It's close enough to when we're getting down into the tenths So, you know, that's a lot better than hitting a start timer So I'm going to say the red one's still a little faster But I'm going to try it just for fun on the other side of the track and we'll see if that's any faster Okay, now we're on the other side of the track. Now. Let's try this seems a little sluggish over there fastest lap 0.85 seconds Slowest lap 0.65 seconds Chevelle average lap time 2.06 seconds Wow 2.06 seconds and the fastest lap was uh Well that 1.85 Holy crap Okay, let's try the blue one and remember we didn't run a practice on that side so reset We're just going to go ahead and start it out Here we go Countdown started Five seconds. All right, let's let's start this again. Three, two, five seconds That's how it is faster. I can tell that I don't know why 2.21 So that's pretty close 2.21 now The the fastest times faster. I'm going to go ahead and run this one again 20 laps And we'll see if the average will be more than the 2.06 Here we go. We're going to try it without crashing this time. So it'll be more fair I Answered that question. Let's off camera. Okay, and one second That's the fastest for lap one 2.67 seconds Chevelle average lap time 2.02 seconds Okay, well there we go So yeah, so far the fastest lap was done with the blue car at a 1.74 so But the average is a 2.02 and that's you know non-stop that's without crashing and the red car is 2.06 They're pretty well evenly matched Uh, except I think the blue one might be just a little bit faster But not by much. So they're pretty well even so Uh Yeah, that's that's pretty cool. I don't think I can have a race with by myself because I'm not that I don't think I could Keep them both going, you know at the same time Without crashing one of them, but yeah, so that's That's pretty good though. Um Yeah, all right Okay guys, so there we go I'm gonna call that a day. Thanks for watching my little uh Race track video that's some stuff to do outside, but On the other day it rained for 24 hours straight And then it got cold. It's kind of cold today. The sun's out a little bit, but I guess they're they want to release her mom they're Um, so she had me open her bedroom door and turn this heater on We have a heater in there for her so In case we need to turn it on but usually if we turn this on out here the heat goes back there and she's fine But on cold days like when it gets down in the 30s, then we turn the one on her in her bedroom. So But yeah, so that this is a lot of fun messing around with these things. I love these little taiko cars, man. These things are in mint Mint condition. I mean the tires are great um They're starting to get They're starting to get where they may need to be replaced sometime in the near future but Yeah, they're in really good shape Could use the The pickup brushes pickup pads pickups whatever could use them cleaned a little bit but other than that I mean they they work fine every time I get this track out and set the car down I don't have to nudge them to get going and just pull the trigger and they go So all right guys stay tuned for more videos. I don't know what my next video is going to be I'm kind of wanting to do a camp out Maybe out here in the backyard, but We'll see like I said it rained all weekend. So I couldn't do it. Well, I started raining Saturday morning Wasn't supposed to start until Saturday night, but it started raining Saturday morning and um I always clean these up, you know before I put them away too Uh, it didn't stop raining until well Sunday afternoon When it stopped raining so All right guys again, thanks for watching. I appreciate it Hopefully Everyone's Christmas season is going well Any hairs that it may pick up get them out of there so all right, I'm going to get a Q tip Clean this out in here on both of them and I'm going to put them away That's going to be it for me today. So we'll see you guys the next one again Thanks for watching. Appreciate shape barely met the main legend gone for now.  Have a Merry Christmas season Whoops And I showed this in my last video, but Here's a good way to find out I got the blue one up front because I think it's a little faster than the red one So let's go see if the blue one will catch it Catch up and lap the red one. Let's find out our answer The blue one has laps the red one and is now Pretty much pushing the red one. There we go Thanks again guys


In the fall of 2019, a subway fare hike in Santiago, Chile set off some of the most violent protests in Latin America's recent history, and with the media dubbed the social outbursts, rioters destroyed churches, metro stations, and toll booths. The protests culminated in the election of the 36-year-old leftist president, Gabriel Boric, who has pledged to nationalize Chile's private pension system, raise taxes, and create a more green economy. Even before that, protesters went after the Chilean constitution itself, in a nationwide referendum held in October 2020, 78% of voters opted to replace it. On September 4th, they'll return to the polls to approve or reject a new draft constitution, which, if passed, could bring a tragic and decisive end to Chile's so-called economic miracle that turned the country into a model for how free market policies can benefit the poor. The current constitution was adopted in 1980, when Chile was still one of Latin America's poorest countries. Over the next 40 years, the government tamed inflation, privatized industries, and slashed tariffs and red tape, which caused its GDP to soar and poverty to plummet. Staples of modern living like TVs, refrigerators, and washing machines became a feature in almost every home. Here's the problem. Chile's 1980 constitution was adopted during the military dictatorship led by General Augusto Pinochet, who took control of the country in a murderous 1973 coup. Because of this, some say the constitution is illegitimate. The best way to address problems with the document is not to scrap it all together, but to revise it, which is exactly what's happened. Since a return to democratic governance in 1989, the Chilean constitution has been amended 140 times. Rewriting the constitution, as an elected body has been doing over the past year, has predictably created a feeding frenzy for political interests looking to codify special rights and privileges into the nation's most important legal document. The Economist describes the country's draft constitution as a fiscally irresponsible left-wing wish list. It bans job insecurity, expands welfare programs, mandates gender parity in all public institutions, and grants social rights that would expand the role of the state in healthcare, education, and housing. The document permits property and asset seizures by legislative decree, without compensation for rightful property owners. It constrains the mining industry, eliminates school choice, and would disband the Senate, making it easier for the executive branch to circumvent the opposition and enact its agenda. These provisions are spelled out in almost 54,000 words, which is about seven times as long as the U.S. Constitution. Unlike that document, which has been in place in 1788, the Chilean draft constitution focuses on expanding state power rather than constraining it. Chile's draft constitution is even longer than Venezuela's, which was redrafted by Hugo Chávez's administration during his first year in office, and set the stage for the country's socialist revolution, the sent into dictatorship, and ensuing economic collapse. Venezuela has had 26 constitutions in a little over two centuries. In general, the practice of scrapping and rewriting constitutions helps to explain Latin America's relentless political turmoil. A constitution provides legal stability and predictability, like a computer operating system. Tampering with any foundational code creates security holes that are easily exploited by political opportunists, looking to amplify their own power and overturn the established order. Even if Chileans reject the new constitution, and thankfully, polls indicate that they probably will, Borges can choose to start the process again with the election of yet another constitutional assembly, to draft yet another version. That could bring years of chaos, economic stagnation, and legal uncertainty. Now that Latin America's free market experiments and economic miracle is coming to an end, hopefully the rest of the world can learn from the experience of Chile once again. Beware, leftist pipe dreamers.


It is my esteemed pleasure to introduce you to Nora Scott, who is the Gommel family professor and senior associate dean in the College of Business at Oregon State University. We're thrilled to have her here. She has research expertise in the area of sustainable business, business law, environmental law, and graduation. And also an international renowned expertise in artificial intelligence and AI, so we're really excited to have her here. I believe I sent a recent article link for her. She has a recent publication from 2024 in the Journal of Legal Studies Education about meeting the challenges of generative AI, and that she's here to share with us in the title of the presentation. Here's what now. We're designing the area of generative AI, and so thank you professors for being here today. We are recording the session today, so we will leave the link available to you to share widely. Thank you. Well, it's a pleasure to be here. I love talking about generative AI, and I know it can span a huge range of folks from those who are not using it at all, maybe to some folks who are familiar, or maybe you're setting up your own GPTs or using it to create chatbots, and we have all sorts of stuff going on where I'm at. I am part of Oregon State University, and when the original chat GPT was launched, I was the associate dean for teaching and learning, and my heart is very... So I started getting a lot of emails and questions from faculty who were saying, oh, I'm seeing it, so I teach in a business school. Google is saying red alert. There's a lot of fear, anxiety, or questions about what this technology is going to mean for us. So I guess I was sort of an early adopter. I started using chat GPT back when it was still free to everybody, and then I got a premium account when those became available, and I have found at this point it is deeply integrated in just about everything that I do. So I use it to help me plan my syllabi. I use it to help me plan meetings for my leadership team. I use it to help me crunch budget numbers. My husband's also a K-12 superintendent, and he uses it all the time, and we talk a lot about the promise of AI for providing individualized instruction and support for students, and so we're both really excited about the potential for AI. There's a lot of concerns about bias and inequity. We're really excited about the promise of AI to actually help address some inequities and provide more support and more structure for students who don't necessarily get it right now. So I'll just set it up that way that I am not fearful of AI. I think it has to be regulated carefully, and we need to think deeply about it, but I am really excited about the promise that it gives us. So I think I want to just have a few words so that I can hear a little bit about your experience of AI. So if you can think about, I'm going to have you do a little, it's Center for Teaching and Learning. What's your program called here? Center for Teaching, Learning, and Scholarship. Your group will approve, so we're going to do a little active learning. Everybody needs to think of one word or two words to describe your personal experience of AI, and you can write them down. If you have something open, you don't have to, but just think of a word, one or two words, and then we're going to share our words out. Let's see, anybody want to volunteer? Should I call in people? Yes. Fear. Fear, okay. That's always one. Fantastic. Fantastic. I love it. Yes. Imitative. Imitative, okay. Middling. Middling? Okay. It's like kind of, yeah. I can't do everything. Okay. All right. Unrealized potential. Unrealized potential. I said it could be two. He had permission. She said a word or two words. I said a word or two words. I did give permission for that. Cyborg. I love it. I wouldn't mind being a cyborg, I think. Yeah. Efficient. Okay. Great. Handy. All right. It's good. Your objectives, your perspectives and experiences everywhere from fear to unrealized potential, that's pretty much what I think is true for most groups that I talked to and for most folks in higher education. And I think that's all realistic. I think everything that I heard is all totally realistic from the fear of what this could look like and what happens if we don't regulate and we don't think adequately about the impacts of it and we sort of just let things happen things happen organically, right, all the way up to, yeah, this can be an incredibly powerful tool, and we have only just begun to think about how we can use it. And similarly, it's not just going to fall into our lap. It is going to be a tool that has to be very consciously and deliberately adopted and thought about how you want to adopt it. So I'm just going to talk really, really briefly, just so that we're all on the same page about how these things work. So my dad was a professor at the University of Buffalo in computer science and then artificial intelligence and engineering, and he's been among all of those disciplines. So I was just, I just saw him this weekend and he helped school me a little bit because I had a couple of things wrong. So you got to always go back to dad always knows right. So just a couple of tips about what generative AI is and what it does. So generative AI, we have to distinguish first between AI and artificial general intelligence.  We do not have that, that does not exist. There is no general artificial intelligence in the world. And there are some folks who are deeply skeptical that we will ever get there. And then there are other folks who feel like maybe it's five or ten years down the road, so there's going to be a lot of difference. But the stuff that people are most scared of doesn't exist. So the computer that's going to make some decisions for us and maybe take over our society, that would be the artificial general intelligence. And that's not out there. So if I can take that off the table for our fears. So what we have are different types of artificial intelligence which are limited. And they're basically, I just think of these as tools that can react to their environment and then produce something in return that we have asked the machine to produce, right? So we've given it some clues about what we want it to create. And it's doing that, but the really amazing thing is that it's responding to its environment. It's taking contextual clues, it's taking in information, and then making a response. So generative AI is basically, I like to think of the large language models. Those are like Chat, TPT, Gemini, if you've used Copilot, which is integrated. There are a lot of different Lama, Claude. There's a lot of different types of large language models. There are different people, different companies own them and utilize them. But the large language models basically just imagine dumping everything in the internet and all of the language primarily in English that is out there and you dump it into the same database. And then you give it to the machine to learn from it. So what it's gonna do is it's taking this huge database and then it knows how to create data as an output that is based on the contextual clues that it's learned from what's in its database. So it has learned from us, right? What it produces, you can think of it as crowdsourcing. You can think of it as a most likely outcome. You can think of it as sort of just looking at the context. So the way the word strings actually come together is sort of fascinating. Because what that huge model is doing is actually saying, when I see the word and, what are all of the things that I know about the word and? Well, it's usually got a noun on either side of it. Well, it usually appears in this place in the sentence. When I see the word generative, I know that a lot of times the word AI is after that, right? It's got all of these but thousands of them, tens of thousands of clues. And then it takes the questions that we give it and it comes out with the most likely answer based on the information that we've given it. So we can think a little bit about what are the problems that will come out of something that is crowdsourcing answers to our questions. Let you think about that for a second. But first, okay, so how do these new machines actually learn what they're doing? I like to use images a lot because they can help us understand what's happening at a textual level. Imagine that you are a computer and that you need to figure out which of these things is a golden doodle and which of them is fried chicken. So this is actually quite difficult. If you're someone who loves memes, you can look for a pit bull or a potato. That's a really good one, a doxen or a doughnut. But they're surprisingly complicated. And so it's gonna try to figure out, very often based on contextual clues. Well, I don't usually, so this rate. So here's a particular challenge. I usually see dogs, I know it's a dog if it's in the grass, that's probably not fried chicken. But here's some fried chicken that has green next to it, that's confusing. I think of fried chicken being in a bucket, but this guy's in there. So it's gonna make guesses and then it gets trained by humans. Humans have to go through and they rate the answers that it gives and they tell it if it's right or wrong and it learns, okay? So this is happening on a tiny individual level here, you can see this example. But this is happening on a massive scale for the large language model. Okay, so what are the limitations that we can think of based on understanding that this is a crowdsourced model? This was an image I asked a program called Dali, which is one of the image generating programs. This was actually about six months ago, maybe seven months ago at this point. I asked it to make an image for me of a college professor surrounded by a group of students. Dali at the time was not very good at hands.  But what stands out about the college professor that it has created? It's a white man, he's of a certain age and of a certain girth. And surrounded, right? He's the sage on the stage and the students are all a little bit alien like. But again, they're sort of white-ish and young-ish for all that they're a little alien. So that to the computer was the most likely reasonable, helpful outcome it could make when you say show me what a college professor looks like, here's what a college professor looks like. And there are indeed many college professors that look like that. There are also some that don't. Okay, so what does it do now? It has been improved. This is Dali just about a month ago, same query. But this is what it gave back to me most recently. So woman now, the students are more diverse. They're still young. She's sort of in like a classroom that looks a little bit more K-12 to me, maybe than a college. But that's very different, right, than this previous image. See if I have another one, I asked it to try again. Still have some wonderful issues with like the legs, right? So not sure whose legs those are or where her legs went. But this, when you look at the caption that identifies it, it actually identifies this man as an African-American professor. So it is, and those are the first two images that came back to me, right? So clearly there has been a change, and it's in the up or down votes and the helpfulness factor that all of those human people who are rating how well it's doing that are training the AI are telling it, hey, we don't want to replicate some of these existing biases the same way. But what is so fascinating about this to me is that you can see so clearly how it has changed. And that is both pleasant in some ways and disconcerting in other ways because it shows very clearly that what it is going to come out with, the generative part of the generative AI is very susceptible and is created by humans. Human agents are intervening, right? So we need to know that. We need to understand the technology is not, the technology is not God-like. We have control over this technology, so it is incredibly important for us to understand the technology and be in a position to teach our students about the technology and how it's going to work. Okay, so that brings me to what I would consider the essential skills for an AI-assisted future. So when I talk and I'm at a business school, so we're not as nervous about talking about the fact that we're preparing students to go into jobs, but I know that makes some people uncomfortable. But, you know, when we think about how are we preparing our students to walk through the door of their job, are they prepared? I don't worry that they're going to be replaced by a computer. That's not my fear. My fear is that they're going to be competing for that job with somebody who really knows how to use AI really well. And they are going to be less efficient and they're going to be less effective at their job. So that is why learning these tools is so essential to our students. Again, they're not going to be replaced by computers. There are jobs that will be replaced by computers, but the jobs that they're getting, by definition, have not yet been replaced by computers.  So what are the human skills that will remain? I'll come back to this picture because it's great. So the essential skills that will remain, think about what do we do in context that is essential? So what the AI lacks is context, human connection, communication, and the ability to truly innovate and think cross-disciplinary-wise. So what are some things that I think we need to really focus on with our students? Well, the number one thing is critically assessing AI output. So I'm going to go back to this picture for a second. So I asked the AI to create an image for me of the evolution from human into robot, the cyborg, right? And I was thinking of that. There's a famous picture of the evolution, right, from the ape to the human. So I asked it to create a picture in that style and to go from the ape to the human to the robot and then it threw some super interesting things in there, like a fish head. Why? No idea. I definitely did not tell it to put a fish head in there. So AI does some weird things. It is not always right. So being able to critically assess that AI output, knowing our own field well enough to be able to assess what it does, is essential. We are not done teaching students. They still have to learn what the content is, but maybe not the same type of content, maybe not as much content, and maybe the thinking skills are more important than some of the content. There's some content that's still essential. I'll talk about what I think that is. Okay, so critically assessing AI output tops on the list. Can't see it as much because it's in yellow there, but on one side you'll see communication and on the other side you see language and writing. I talk to students a lot who are really nervous and I talk to journalists and students. I talk to students who say, my voice won't matter. If everything is computer generated, it all sounds the same. It just takes all the life out of everything. I'll say two things in response. One of them is your voice is going to be even more important now because if you are, and this is particularly true for our marketing students, our communication students, our literature students, our journal students, everything, they're going to be swimming in AI created content. Their unique voice is going to allow them and their content to stand out in a totally different way. So create your voice, your unique voice, just as if not more important than ever before. And the other thing that is important is understanding our own communication because we are communicating with the AI. So part of what we have to understand and we're going to have to learn how to break down are what are all of the pieces of information that we're giving when we ask a question to AI, we call them prompts, when we do a prompt, what are the things that we're saying and what are we not saying and what did we forget to say but should have said. So sometimes the language that we use will communicate something to the AI that we did not intend to communicate. Sometimes we will fail to communicate some essential information. All of that are language skills, that's all communication skills, all incredibly important for our students. Learning how to engage in team building, communication, how do we emphasize, how do we form relationships? We hear all the time from employers how incredibly important that is and we're already not doing as good at it as they would like us to be, right? That's always consistently if you're familiar with the NACE competencies. One of the tops, those are the skills that employers would say students need. One of the top ones is always groups. How do we work in groups? How do we do relationships? How do we manage projects? All of those skills are absolutely essential to our students. Engaging in problem solving and then the ones on the bottom I'll talk a little bit more. Addressing bias, making innovative leaps, so retaining the ability to engage creatively as human essential for us. That is how change really occurs and if we stop prioritizing or don't think about how do we deliberately and consciously embed that in our curriculum, we're gonna be in trouble. And then the last words, the last group is magic words and then content specific knowledge. I'll talk about that too. So let's talk about bias for a second. If you haven't used chatGPT, this is what kind of the string looks like. So there's a spot for you to ask a question and then it'll provide these nice responses. So back when I first started playing with it, I liked jazz. I would ask it for a list of the top 20 jazz pianists and they were always all men. I would just spit out this very comfortable list of usually the same folks. And then maybe two or three months ago, I started like a woman would pop in every now and then. I'd be so excited. And it would actually start giving me more context. So now when you talk to it and you ask it, give me the top 20 jazz pianists. It says, listing this can be subjective as it often depends on personal taste, the era and the style of jazz. So it's actually learned how to give context to the person who's asking the question. It is improving my question in its answer. And I can actually ask it to improve my own question. So I can put in the prompt and then I can go back and say, what would have been a better prompt? And it can actually figure out an answer to that. So now it is giving me context as a list for me but here's where I can query it and try to get in and dig into some of this bias. I noticed there's only one woman on the list. Why do you think that is? Well, it actually gave me a really good response because it told me here some of the factors that you should consider. Historical exclusion and gender bias, limited visibility and recognition, social and cultural norms. This was not the whole answer but I picked off a piece of it. So it is able to analyze its own biases to some extent. So we can teach students that are using generative AI to also use generative AI to question themselves and their biases and the biases and the responses that they're gonna get. Because we exist and we walk around in the world and have all sorts of embedded unconscious biases. We live in bubbles, we all know this, research well. We don't even necessarily know where we are asking questions that are limiting the output that we're getting. And so being able to engage in some of these dialogues can actually be really beneficial. I do work in sustainable capitalism so I put in a query here, is capitalism linked to white supremacy? That by the way is an image of a capitalist. So I asked it to give me a capitalist, that's what it gave me. And so it gave me a pretty complex response. The question of whether capitalism is linked to white supremacy is complex and multifaceted on the babies and output. Now I've asked this question in different ways as well. I've asked the question, explain how capitalism is not linked to white supremacy. Different response, right? Totally different response that I'm gonna get. I can ask it and I can say, how is capitalism linked to white supremacy? So this is where the communication skills are so essential because each one of those questions is gonna give your students a different answer. It's gonna give you a different answer if you start using this more. So it allows us to actually look into our own selves how am I changing the output? Think about research you might do. How are you changing the output of your research by the research questions you're asking? Okay, so what about content? What do we teach? What stays? What goes? This is probably the hardest question that we have in front of us. And I'm happy to talk a lot more about some ways that we can use it for sort of non pedagogy and not in the classroom, but just to pause on content for a moment. So when I talk to faculty about their courses and what dictates what's in your syllabus, I would say that the number one thing that dictates what in the syllabus is not, this is what my students need in order to be successful after they graduate. It's more like, well accreditation or I'm the prerequisite for this class and they said they needed this or the textbook does this or the person who developed the course and I don't have control over the course that did that. So this is not new to higher education. This is not a new question that we are struggling with. What content stays and what content goes? Are we teaching the right things to our students? This is something we should be struggling with in all of the contexts, right? Not just AI, but the AI really sharpens the problem. So when we think about what content stays and what content goes, this is my framing and the article that I shared with you all kind of takes this idea and this framing and fleshes it out more. But basically I will look through and I have broken out types of content into these buckets and said this type of essential content needs to stay in our curriculum and by implication the stuff that doesn't fall in a bucket probably could stay. There's the right place for it or reason for it but it doesn't have to, it's not essential. Let's talk about what each one of those are. So I teach law and these are some examples from law but you'll find these are really very discipline specific. So I can't tell you what is essential content for a chemistry class or a marketing class or a literature class, right? I can only give you some examples from my experience. So the first bucket that I talk about is structural basics. How is the field organized? We can think of this as sort of the medic cognitive level of how do I think of and conceive what happens in this discipline? And we probably need to teach a lot more of this anyway. This is really important for particularly for first generation students, for students who are not coming into our context with a really privileged background where this stuff is second nature to them. This is teaching us about what the structure is that sometimes we ourselves are blind to and it forces us to break things back down into component parts that we really think about what are the structural basics of our field? So for me, that might be things like what even is a legal theory? What does that mean? If I talk about the elements of a legal claim, that's how we break out and how we prove things in the law, I have to teach students that. They don't walk into my classroom knowing that, okay? And then I can think of key content areas and those key content areas are basically areas of content that are either themselves and by themselves essential or they can serve as an analogy for a way to learn something else. So I put intellectual property or IP on there. Students about trademark, I can teach them about copyright and they can find that there's a very common pattern. There are state statutes, there are federal statutes, there's statutes, there's case law. I can teach them how to read a case. All of those things, I can teach them for that particular content but then when they are learning employment discrimination, they use that same structure and they can actually really teach themselves a lot of employment discrimination law. I don't need to spend a lot of time teaching them employment discrimination because they can use those computers in their hand that they bring everywhere we go. They don't need to memorize the rules for employment discrimination. They can look it up on the fly because they know how to learn. They've learned that tool, that metacognitive process. So having some key areas that are analogous to other things and then I talk about magic words. I actually got caught by this. I was talking to my dad about this one again and he said magic words. What does that even mean? I said, oh that's funny because magic words are actually magic words. In the law, you call something a magic words when they have a specific meaning. So the phrase, what is a reasonable person? That has a specific meaning in the law and court cases actually refer to magic words. So magic words are magic words. And I thought everybody knew that. Apparently you don't, I'll know what magic words are. So I didn't just make that up, magic words are magic words. So what are the key phrases that actually change the outcome of your queries? And for your discipline, if we were gonna do a workshop with your faculty, you can break it down by discipline and you could say for your engineering folks, for structural engineering, what are 10 words that if they don't know what those words are, don't know how to use them in context, they're gonna get the wrong answer if they put a query into a box somewhere. So we need them to know these essential concepts. Example in the law, the reasonable person and reasonable accommodations. If I ask chat GPT and I say, one of my, I have a small business, I'm a small business owner, one of my employees has asked to have a device that allows them to speak to text, right? They want one, is that reasonable? Okay, think about that. Now I could also ask it, same thing, my employee has asked for this device, is that a reasonable accommodation?  That's very different than what's reasonable, which is not necessarily connected to the Americans with Disabilities Act. So those are really important concepts that are gonna be unique to each discipline, okay? And then really at the, again at the metacognitive, at the problem solving level, how do students and how do you want them to make decisions in your discipline? How do you want them to go about engaging in problem solving? In the law, we have a very specific, people talk about thinking like a lawyer. We have a very specific way we go about doing that. Science, of course, has a very specific way that we pose questions, the scientific method. We want our students, they don't know that biopsmosis. They have to be taught these skills. So we need to identify them for our disciplines and specifically teach them to our students. So within those structures, how do they test the concepts that the AI has given them? Well, in the law, I wanna teach them, here's how you find a real statute. Here's how you find a real case. Here's what it looks like to read a real case. Let's get the experience of reading a real case. What are the reliable websites I would send them to where they're gonna be able to test the information they've been given? Decision making, when students are making decisions, I want them to think in this sort of trifecta of what are the financial risks of a business law decision? What are the legal risks and what are the strategic risks? That's a decision making framework that I want them to use when I give them a complicated hypothetical. So what are the decision making frameworks that you want them to use? Because if I go back here, problem solving is one of the key elements that students need. We hear this all the time from employers. I don't want a student who just knows how to do one thing. I wanna be able to give them a complicated task and have them figure it out. They don't know that just by living. They learn it, right? We have to teach them. And then we really need to know we're in our disciplines. Again, very discipline specific. So bias exists in all sorts of places in the legal system. Some of them were very deliberate for a long time. White men were the only ones who could serve on juries. There are laws that excluded people from ownership of land, right? So we know what some of those look like. But as a business owner, bias might show up in my hiring practices. Bias might show up in my governance structures. It might show up in the way that I structure my product offerings. And then when I know what those areas are, when I ask ChatGPT, can you come up with a new product or develop a marketing campaign? Then I can also ask it, how might this cause a biased result for certain customers over others? Because I knew what question to ask. I knew that this was an area of potential bias that I needed to be thinking about. This is for the real pedagogy geeks in the room. I don't know how many would identify that. But our online learning service came up with this new Bloom's Taxonomy that I think is actually quite helpful. And what it does is it actually looks at, for each of the different levels of Bloom's Taxonomy, which we already applied to the way that we put our courses together and the learning outcomes that we use. And it looks at what about that skill can be done by AI and what cannot. And then asks, okay, so when you are integrating this into your class, what does that look like? If I have one of my learning outcomes is that I want students to be able to remember something, well, the only thing that is really unique about this is if technology is not available. Technology is available, students do not need to own that task. So this is a really helpful tool and I'm happy to share it online. And I think it's got a Creative Commons license on it. So you're welcome to use that yourselves. Okay, so my ideas for how to integrate AI into your teaching. These are things that I have done with students and that folks in my college have done with students and found to be really fun. Looking at AI responses for areas of bias. So Oregon State University has a license now with Microsoft so we have access to their co-pilot in a private. So you all will have to figure out how comfortable you are and what rules for students using these tools. Cause that is something that you have to figure out, right? But, so if students use AI, can they have it analyzed its own or is this just a fascinating thing to ask it? What might have shown up in your response that was biased or why? The next one where it says take AI text and rewrite it so it's less than 40% AI generated. So I was actually the college hearing officer for my college and so I dealt with all of the academic misconduct cases for five years, including the start of the chat GPT revolution. And one of the first responses we heard from some people, the goodness not most, I would say some, was it's all just plagiarism. They're all just cheating. The first thing I need is a tool to catch the cheaters. And there were immediately a number of these plagiarism detectors, turned it in, came up with one, it was terrible, it removed it. But there's one called zero GPT, there's one called GPT zero and you can put in text and it will tell you the likelihood that it was generated by AI. They are not reliable and they are biased against English language learners or folks who don't speak English as a first language. So I strongly urge you do not use them for academic integrity cases to prove that a student cheated. But here's where they are really valuable, is that students can see in their own text how much they look and sound like a machine. And then they can look at it and say, I'm not very valuable if the machine did all the work here. So in business we talk something, what's your value add? Like what did you bring to the party? And if what you brought to the party was about 10%, I don't know that I need you, right? You're not that valuable to me. And I don't know that your writing is gonna stand out, I don't know that you really understood what you wrote about. So students can do this themselves. They can put their text in, they can edit it, and they can see what does it take to get it so it's less than 40% AI generated. A presentation or an infographic or even an essay targeted to different audiences. So this is absolutely fascinating.  Now make me a presentation. And then you could say, my audience is going to be mostly Hispanic, first generation folks who have primarily a college education. That's gonna be different, right? You can target and what the students will see is what is the impact of your bubble, right? On what is persuasive to you, and probably what you're hearing from sources. Because what the AI is doing again, it's not doing something that it came up with. It is reflecting back what we do. It is reflecting back what humans do. And it's saying, oh, let me figure out in my database what looks the most like that group of people and the way they talk and the kind of material that is aimed at them, right? So it's been an illustrate for you your own biases by having it target to multiple different audiences. Been talked about quite a bit, AI makes things up. Just like you put a fish head very randomly on something, it makes things up, okay? And so you always, always want to caution your students that they always need to double check. Particularly if it's sort of a journal article, something with a page number on it. Think about the way that it works. It's telling me, when I see this series of letters, it's usually followed by this series of letters. So it comes up with very plausible article citations because it's like, there's usually a number. There's usually a name, right? It can say, Anara Scott, oh, she usually publishes in this journal and there's usually these numbers. But it's like 21 instead of 20, it's just made up. It's just making stuff up. So have students look for reliable sources. Use AI capabilities to increase the scope of an assignment. Your students are probably using AI. I think something in the latest survey I saw was something like 65 or 70% of students are using it. Only I think 30% of professors were. So we got to catch enough to do, right? We need to be conversant with the tools our students are using. But one of the great things is that instead of saying, okay, the only way I can do assignments is I'm gonna put my students in a room and I'm just gonna give them pencil and paper. I'm just not even gonna let them access the internet. And that is a technique folks use. What if instead we recognize, this is the tool they're gonna be using in the workplace. What does that mean for the capabilities that they had, for the efficiencies that they could gain, for the different ways that they could go about a task? So instead of assigning groups of students to come up with one business product idea, have them come up with 20. And then they've gotta do the task of assessing for our region and what is popular for us in the Pacific Northwest, what would be the best of those products? So making assessments, again, of the AI output. We need to learn how to use AI safely and responsibly, so do we. One thing we can do is we can teach them more about what prompts look like with different large language models and the differences that small changes in the wording. So my query about white supremacy, show me how it's linked, show me how it's not linked, is it linked? Three different queries will provide three different responses. Have students change their own queries to think about what that does to the output. Develop scaffolded assignments that teach students how the LLM can provide them with feedback. So one of the most wonderful things that this technology can do is it is a built-in tutor for your students. You can't provide the kind, we would all love if we were sitting in a classroom with three students and we could just mentor and so we could socratic talk to them back and forth. We can't provide AI, I can't. So think about what you could have them do to get feedback on their work. Then you can have them provide you a copy of the chat so you can see how they interacted with it. So some ideas might be start with an outline of an essay and then ask the LLM to provide feedback on your outline. Then show me, Professor, how did you change your outline as a result? What were the changes that you made? Have I give you feedback? What do I need to do different things with my sentence structure? What's some general feedback you can give me about my writing? Maybe it's a math assignment. I keep getting these problems wrong. What am I doing wrong? It has a built-in ability to look at students' problems where they're struggling and provide one-on-one feedback and attention. Again, that we as faculty would love to give them but we just don't have the time. We have too many students to be able to do that. So this is where it can be really a powerful tool, frankly, about that one. Okay, and then finally assessment. Your students have the ability to cheat on every single assignment that you give them. It can pass the bar. It can pass neuropsychology entrance exams. You are not gonna come up with something so clever that the AI can't figure it out. It's gonna be able to figure it out. Now, it might not do very well at it for a whole variety of reasons. And so I know a lot of faculty who will say, that's fine, if you wanna work with the AI, go ahead and do it. And they find that the students who use the AI exclusively, who don't engage in a back and forth with it, who aren't applying their own critical thinking to it, don't do very well. Because it's just crowdsourcing. It's not responding to the contextual clues of your classroom. It's not responding to the individual ways that you teach and that you're looking for. So they can cheat, but they probably won't do great at it. But they can cheat. And particularly if you use multiple choice questions, if you have something that has a black and white sort of answer to it, it's gonna be really good at that. So what does that mean if your students can cheat? We could play an arms race to try to outwit them. I tend to think that's not the best use of our time or resources. I would rather that students see the value in each with those assignments because they see the value. Your students do not want to waste their money or their parents' money or a family or a scholarship on something that they think is useless.  They actually wanna learn stuff. They really do. So I really think that because I hear that sometimes and I tend to think we've actually done that to them because we have taught them just sit and repeat, just sit and answer the multiple choice questions. Just play this back by road. They learned it in high school. They learned it in grade school. And then we come to college and we're like, oh, now you should explore ideas because of the love of learning. It's a little unrealistic, right? We're asking more of them than perhaps is fair. But if you show them, this is actually gonna be essential to your success in your job. This is gonna be essential to your ability to solve problems. This is gonna be essential to how you interact with other students in my class. Now that they see the value of it, that is gonna create a different response in your students. If you're assigning busy work, no, your students are not gonna feel any particular, do you love doing busy work? Do you respond to all the emails that you get? I think you don't, right? So we as humans do not like feeling like our time is being wasted. And that's fair. So our students, if we're gonna assign them work, it is fair for us to explain to them why we are assigning that task and why it matters. So engaging students, finding ways to deeply engage them in the material, that's important. If your class focuses on the lower ends of Bloom's taxonomy, that's gonna be a particular challenge. Those are the courses that are gonna need the most revising. And then the final bullet, and this comes out of doing a lot of academic integrity cases, is that we ourselves need to understand in advance how the technology works so that we can adequately communicate to our students what is okay and what is not okay. The most unfair thing that we can do is to have students think, I was using Grammarly, isn't that okay? Everybody uses Grammarly. Oh no, I don't let you use Grammarly in my class. Well, how was I supposed to know that? Well, you should just know that. Just because it's plagiarism, it's cheating. And so for many students, that's how it feels because there's a whole spectrum of ways to use this technology. You can plug in, write an essay, blah, blah, blah, right, and it can spit out a whole essay. That's very different from, I just wrote this outline. Can you give me some feedback on my outline? That's very different from, here's my finished essay. Can you give me some pointers on my language? All of those are totally different uses, but if we as faculty don't identify what is okay and what is not okay, we are setting our students up to fail. And that's not fair to them. But we have to understand the technology well enough ourselves to be able to communicate that. And the last thing that I'll say, and I'm sorry not to leave more time for questions, but this was a, I was having some fun with images in Dolly. So I asked it for some images about jumping onto a speeding train. And it took, I actually had to tell it to put a woman in there. It was, it did not, it does not think that women jump on speeding trains.   I said, please make an image of a woman jumping onto a speeding train. It's going really fast. The technology is changing incredibly fast. And our temptation may be, I'm just gonna wait until things settle down. And then once things settle down, then I'm gonna give it a try. It is gonna be impossible to wait for this train to stop. It is developing at an incredibly rapid rate. And the only thing that you can do is jump on and join it midstream. You're gonna fail.  They're not gonna work very well. Your students are doing the same thing. Learn together, share that vulnerability with your students. Hey, I tried this thing out. It went terribly. How did you do it? What worked for you? Learn with your students. Share with them what you're doing. But we all need to be looking at how we're jumping onto the train because it's not stopping and it is gonna be essential. And that is, that's it. We just have like five minutes. Yeah, happy to answer questions. Yes. I've been teaching GPT for almost three years now. And something's come up this semester which I wasn't expecting. And that is students seem to associate stigma with using chat and the team. And I'm very clear saying, use it. In fact, a lot of assignments they're required to. But for the other assignments, they have strict instructions on show me the prompt, show me what it generated, show me how you use what it generated. But students are very reluctant to do it. One of them will try to sneak the chat GPT stuff in without giving any credit. I pointed out that's plagiarism. You're in a lot of trouble. You can have no seas. Yeah, yeah. And but there's a stigma associated. And it's just, I mean it's hard to deal with. Yeah. To say, look, it's okay, you can use this. Yet they seem to feel, no, no, I shouldn't be using this. This is a great question. I'm gonna repeat the question just for the video that we're seeing students who feel like there's a stigma. And even if they're told, I actually have one of my statistics faculty members, he has the exact same experience they can use it. They use it but don't tell him. And he tells them, tell me if you said anything that they don't wanna, still don't wanna tell him. And I think this is incredibly important. So we, and I think the problem is that, so given, so I was visiting with my sister and her husband and my nieces over this past weekend as I'm traveling, every single one of those four people asked me like, aren't you scared of it? Isn't it cheating? So there's this sort of societal fear that either it's really bad for us on some deep ethical level. Using chat GPT is cheating in some sort of life existential sort of way. And I had a prolonged conversation with my niece. She works for a organization called Ceres that does really important work with sustainable business. And I said, well, have you used it in your work there? And she said, no, and it doesn't seem right. And I said, well, you're doing really important work. If this tool could make you more efficient, isn't it unethical not to use it to further the work that you're doing, right? To be more efficient in your job? So I do think you're reflecting something really important which is that there is a societal fear that it is either unethical or, and spoken or unspoken, there are probably students whose friends have gotten in trouble for using it. And so now they're like, ooh, we don't want to, we don't use it, it's cheating. So it just means we need a cultural, we need to have the conversation. Everybody in the university needs to be talking about this. Every faculty member should have an AI statement in their syllabus, every single one. Nobody should not address at the beginning of class what is okay and what is not okay because it's the folks who aren't addressing it that are creating that fear in students that they don't know what's allowed and what's not. So I appreciate you saying that. I hope that that's part of the conversation. Yeah. Maybe one more question? Yeah. So this is all based on training models using historical data. As we are getting on the train, are we putting less and less focus on creativity and coming up with something totally new? I actually, so again, I go back to the conversation about voice with the journalist that I don't think so. I've had wonderful conversations with folks in writing, liberal arts, people who are creating art that is AI enhanced, visual journeys, sound journeys. I think it allows us to engage in a different type of creativity. The models themselves may reflect what came before, but so do we. We are ourselves a product of what we learned which came before. And then it's the way that we put that stuff together that reflects our creativity. So I think there's enormous promise actually to spur different types of creativity and to think about creativity differently of how do we put things together and how do we continue to make those innovative leaps? Yeah, I think that's a common concern. But I really think that there's enormous ability to engage with the AI in a really creative way. I love the argument, we're the same thing. I'm just stuck on the fish head. Yes, yes. That's a good visual, right? I wanna know if you can have an ongoing conversation like could you have said chat GVT or whichever one you use, why did you have a fish head on one of the characters? And would it be able to answer you? Does it have self-awareness of why it does what it does? No, not really. Even the higher levels of the AI are, it doesn't really know what it produced. And it has a very, it knows on sort of a basic level that I was asked to do this and I did this task. But at the minutiae level of how it put something together, you can ask it the same thing multiple times and it is very often gonna give slightly different responses. And I think what the computer is doing is that so each word has these vectors that are associated with it of numbers and the word ant has 17,000 numbers associated with it and then it's connecting the next one together and the next one together. So each time it does that is this incredibly complicated series of connections that it really can't do twice. And it doesn't, it doesn't save. You can ask it, like the question's about bias. Where might your answer reflect bias? It can do that, but it's not good at looking at it's own. So it remembers the question that you just asked me. So it remembers the question generally. It's not very good at remembering its output and it'll forget the question like four or five queries down, like you gotta keep refreshing it. I think that's actually an important common misapprehension or misunderstanding is that people think, well, it's just gonna do it for me. Like I just do it and then it gives me the perfect outcome. Actually getting something valuable out of it can take some time. So you have to interact really deeply with it in order to get the output that you want, which should make us feel better rather than thinking, oh, then it actually doesn't work. You can see actually it only works really well when it's a relationship between what I know and then how I get out of it in response to it clearly. I gave you the scheduling problem. I set up my schedule, these are the adjuncts. I have to quote them and they can only teach it these times and you can't teach three classes back-to-back and all this stuff and they kept making the same mistake. And I'd say, no, that person can't work after 3P, I'll do it again. Oh, I'm sorry, does the exact same thing again. Over and over again, so yeah. I assume eventually we'll have those games figured out. So, Carrie, one more question. Is it like Clif Notes, could a student go, could you summarize chapter four of X, 12, and do it? Yeah, yeah, okay. Yes, it's very good at CAPT. Yeah, it's really good at it, yeah. That's actually one of my concerns because the things that's really good at is all the stuff you teach them like in K-12. Maybe they won't read it anymore. I'm wondering if they're gonna get to us in a few years without us close to do anything because CAPT would be people so easy. I'm gonna say no. Because, and I see what's happening at the K-12, and to the extent that we were having them do book reports on a book, that actually wasn't probably a great use of their brain anyway. That we were, just like our students, we want to push them to upper level of blows. We want to do that at the lower grades as well. So it's the same sort of issues in the lower grades that we're dealing with in our, we're just ratcheting up the complexity of the content. And actually maybe it will be helpful when they come to us because I found one. A couple of years students aren't good at asking for what, for a question, formulating a question to get a good response back. They find that they don't Google well, right? No, that's a skill, right? Absolutely, it's good. But they're actually different skills.  What makes you good at content engineering is much more context and clues of thinking deeply about how you want the answer and what would best address your question and what is background information and all of that. So yeah, but they're only gonna get good at it if we teach it. They're not gonna get good at it magically. Yeah, I was just thinking, looking at how this is all impacting, emerging new programs and certificates and prompt engineering is like the hot topic among the deans and the provost and so forth. And yeah, it just strikes me as an essential skill that our students are gonna need. And as an example of a, maybe it's a job category, but it's certainly an employable skill that some things will be replaced by computers, but a lot of things are being created by this in terms of employable skills that didn't exist before. So. Well, I want something. Yeah, I'll let you all go, but I'll be here if you have more questions and you're welcome to email me a question.


Meanwhile, adaptation planning for the pelagic sargassum influxes and the impact of climate change on fisheries and aquaculture were among focus areas of the recently held 4th Huey Open Campus St. Lucia Country Conference. Details in this report. The second phase of the Jeff SGP-UNDP Knowledge Fair and the UWI Open Campus St. Lucia Country Conference 2020-2021, which included the first national honey show training workshop, have been healed a success. The UWI Open Campus St. Lucia, in collaboration with the Jeff's Small Grants Program, UNDP, will set its fourth country conference under the theme, Visioning Sustainable Futures, confronting the threats of climate change and climate variability, which provided a platform to share existing research and disseminate information on St. Lucia. Commenting on the clues of the 3D conference, UWI Open Campus St. Lucia's head of site AG, Mistress Leslie Crane-Michelle, opined that while it was their fourth country conference, it was the first virtual conference. It was our fourth country conference, but of course it was our very first virtual country conference in keeping with the various protocols that we now all have to follow. The conference was a wonderful success. It took place over a three-day period. It began on the 15th, the evening on the 15th with an opening ceremony. The conference saw presentations focused on a range of climate change-related topics, including historical and future trends of climate-related hazards, St. Lucia's climate policy environment, towards concrete action. The impact of climate change on fisheries and aquaculture, sustainable harvesting of the intensity, adaptation planning for pelagic sargassum influxes in the Eastern Caribbean, a St. Lucia Key study and the Eastern Caribbean solar challenge. All of them focus on climate change, but you basically have key areas represented. So the solar challenge, for example, that is facing the region, that was a big one that was focused on by the OVCS. The huge problem that we've got with sargassum in all of the islands of our region, really, and of course in St. Lucia in particular, was paying a lot of attention to. We also had a number of presentations, also from the OVCS, and Ministry of Sustainable Development, which focused more on the various policies that need to be put in place if we are going to make any inroads on the climate change problem that we are currently experiencing. So we did have a wide cross-section, and we had a very interesting one, which looked at more the spiritual impact of climate change on all of us in the region. It was a very special presentation by our very own UWI PhD candidate, and it really lent a very special touch to the proceedings, because there is a tendency to view climate change as strictly an economic, political, and of course a scientific issue. But there is also, of course, the whole social and spiritual impact as well. So it really was all encompassing and a very, very rewarding few days. Mrs. Green-Michelle concluded that the conference was altogether an enlightening three days, highlighting the urgent need for aggressive climate change adaptation in St. Lucia and the wider Caribbean, while providing local and regional beacons of hope within an often bleak global climate change context. In the same vein, the National Honey Show Training Workshop held in February is also being held as a success by the organisers. The two-day event was undertaken to prepare beekeepers and various others in the sector to participate in the Ireland's first-ever National Honey Show, scheduled to take place in December of this year. President of the IANOLA apiculture, Collective, IAC Richard Mathias stated that this is the first activity of its kind directed at St. Lucia and regional beekeepers. While the event was facilitated by four world-class presenters, it was under the tutelage of leading expert and certified honey judge, Ms. Jennifer Holmes. We had a number of very interesting facilitators over the two-day period. Day one, we had Jennifer Holmes, who is an international honey judge. She's based in Florida, and she gave us a really good in-depth three to four hours on really how to prepare yourself for the various different categories. Carla Essin on day two, she gave a nice one-hour presentation on rules and regulations and more on the mechanics of how we set up the Honey Show. I think two Caribbean facilitators were really stole the show. Gladstone Solomon from Trinidad and Tobago, and Dr. Valma Jessaby from Grenada. Gladstone has participated or has spearheaded Trinidad's participation in the London Honey Show for at least from 1987 to over 2000 or 2005, where Trinidad has won participants from Trinidad have won a number of different categories, or they've placed in a number of different categories. Dr. Valma Jessaby from Grenada, who is a multiple winner of the Hender Cup also. She has been a real trailblazer for the Caribbean and diversifying the honey product from the region into a more value-added area, so it was really good to have her on board as a presenter. With a very positive response from participants locally and from around the region, Mafia's fills compelled to make the Allens first to Honey Show a success and concluded that a second seminar will be hosted midway towards the competition date in order to ready participants for the Honey Show. We still need to do some more groundwork locally to get our beekeepers really, really unprepared so that we can really have a really competitive environment so that everybody fully understands the rules and regulations, and we'll probably have another seminar in June as a refresher and to really get everybody acquainted with the rules and regulations and to get a better idea of the numbers of people that will be participating in this year's competition, but at least by setting the stage early in the year in February, beekeepers have an opportunity to start setting aside their best honey or preparing for the various different categories from now, so at least they've got the whole season to really prepare and put aside what they think is going to be their best honey for competition. Pleased with the success of the events organised by his organisation, Jeff Small Grant's programme UNDP, in conjunction with the Caribbean Youth Environmental Network's St. Lucia chapter, the National Coordinator Giles Romulus indicated that it is the intention of the Jeff SGP UNDP that these activities serve as a fillip for the development of the apiculture industry in St. Lucia and the OECS. He also noted that both components provided a valuable nexus with the broader Jeff SGP UNDP knowledge fair ideation component. With its solution-oriented approach to existing and looming environmental threats, which must be urgently addressed if St. Lucia is to have any chance of achieving a sustainable future. From the Government Information Service, Hermione Mark reporting.


The F-35C Lightning II was recently showcased at NAS-Lemour. This aircraft will enhance the flexibility, power projection, and strike capabilities of carrier airwings and joint task forces. It is scheduled to be delivered to the fleet in 2017. A performance-based senior enlisted continuation board is scheduled to convene later this summer. If you have more than 19 years of service, check out navadmin088-15. The littoral combat ship USS Fort Worth returned to Singapore April 15th after spending two months operating throughout Asia. This summer, Fort Worth will take part in the 2015 Cooperation of Float Readiness and Training Exercise series. And finally, after six months of conducting airstrikes over Iraq and Syria in support of Operation Inherent Resolve, the Carl Vinson strike group is headed home to their loved ones. For these stories and more, visit navy.no.


Hello friends, I hope you're all good. Today, we're gonna be doing the first sentence challenge Which I have done once before on my YouTube channel, but it was many years ago It was right when I'd start my book to channel right when I got back into reading I had like six books on the show So we're gonna be doing the first sentence challenge if you don't know I'm blind-holded Someone reads the first sentence of the book out to me and I have to guess what it is Now we're actually playing for points this time We're gonna do point space we're gonna do 20 books in total if I get it on the first sentence I get three points. I can then get given the second sentence. I get two points. I can then get given the third sentence I get one point if I don't get it nil-pois nil-pois. So we're playing for a total of 60 points today and she'll be fun It's gonna be good. We're all gonna have fun. The first sentence challenge is always fun I think we should bring it back I think everyone should do the first sentence challenge again because I think it's so fun. I I'm only mean for like 40 points I would say because I feel like I'm all right at this and I do quiz nights with my patrons every couple months and One of the rounds we always do is first sentence and I get a first sentence from my shelves for the quiz So I feel like I'm gonna be pretty good at it But in order to do this video, I need a helper and my help is going to be Tom! So you're gonna pick the books Okay And I'm gonna be blind-holded and tell you what the first sentence is be kind Pick books you think I may have spoken about a lot and I might know. Why am I so pale? Because I'm orange I look like a ghost May have different complexions. Wow, you're way more tan than me. I'm not tan. I'm red. I'm florid Florid complex. This is gonna be I have no blindfold. So I'm gonna be I'm gonna use my makeup headband Okay, should we just begin? Yeah, okay We're gonna be for 10 years if it takes you as long to pick a book every time. You're horrible.  Kauru. Oh, okay. I know what it is. Is it daughter of smoke and bone? Yeah I know the character name. I can't believe you're really Getting me to read in front of people.  Well done Megan I'm so great at this. When you're packing for a holiday Even sunday can be a source of joy What?  Don't know. What does that even mean? Something obnoxious Okay, I'm just gonna make a guess because I have no idea. Um Holiday holiday Love is a revolution boning. Nope. Okay. Next one I've never been overly fond of Sundays And I usually try to put off getting up to face the day until the last possible moment Fucking Um Uh Watch us rise No, no But this sunday we're preparing for a week away and I was up and doing long before my usual hour One by one by Ruth Ware. Nope.    You can't pick from there No, that's what that was I don't listen listen to me. That's okay. No, I I haven't even read it. What's fair. Right life's not fair Okay, listen to me.  I'm trying to do stuff quietly anything. I can't believe you picked a book. I have any I sit with my wrists cuffed to the table and I think But that I am forbid to tell the secrets of my prison house I could I could a tail unfold whose lightest word Would harrow up my up thy soul. Have you read more than the first sentence?  Yeah, why not?  I I'm convinced I have not read this. What? Come on. Come on. Come on. Um, uh, if we're villains. Yes, what? Oh my god, that's two points I can't believe it sounds like Shakespeare because it it all shakes beer fans. Oh, well, there we go.   That's when I knew that I was born to be great Just destined for greatness So good at this and the fact that could have been any in the series. I knew which one it was I'm genius. I'm genius. I am your maid.  Yeah That's such a bad first sentence I am your maid Dear professor Mansfield, I am investigating a mysterious case and suspect you maybe I was a help Mansfield Mansfield investigating Oh, um mysterious case the Abton Angels. Nope. Oh, okay next one. Let me explain.  What is it investigating? I'm investigating a mysterious case and suspect you may be able to help A twyford code. Aye aye I knew it was one of those. God, I'm so great Emonies when life give you lemons make lemon verbina temblique recipe I don't think that's the first sentence, is it?  Oh, um, um with the fire on high Yeah, is that we're giving me a three point or a two point there? I'm gonna give you a two point Two point. Okay there enough. You've been very very harsh. Nice to meet you Kelly Why do they have all this guff at the start of the birthday?  The moon was high and full. The night was right for the witchy business Danica Brown had honey on her tits No, that that's not the first sentence. The moon was high and full The night was right for witchy business and Danica Brown had honey on her tits. You were joking. Nope.  Just one tip. The ravens. Nope The left one specifically What? I haven't read this have I?  The monarchs? She's going for the other one For fuck's sake.  Danny Brown. Take a hint Danny Brown. Yeah.   I'm sad By the time Alex managed to get the blood out of her good wall coat. It was too warm to wear it ninth house Yeah, it's almost like this is my job. It's almost like you can hear where I'm getting the books from No, I wouldn't I knew I would have known that regardless But I'm trying to tune that out. Most of the books I have no idea where you've got them from You big deco locator I hear a noise Linnet Ridgeway Linnet Ridgeway Linnet Ridgeway, I know that name Give me the next one. That's her Uh, said Mr. Burnaby, the landlord of the three crowns Linnet Ridgeway That's her Oh, is that Death on the Nile? Yep Oh my god I actually am amazed by my own brilliance I'm actually fantastic at this She couldn't remember the first book she had eaten Oh Oh, who's eating books? Who's out here eating books? Uh, I'm just gonna make a guess library of the unwritten Okay, next one. What it tasted like how it had felt the scratch of it as it slid down her throat Oh, oh, um, it's horrid. It is horrid That's a good one. I liked that. Yeah This sounds like an interesting book. That's the one that's a one I'd choose to read most thus far Okay, I have all those first sentences. Okay. Interesting. Tom's and his reader error error guys Not that much The parties at the Toonion's house always ended up unquestionably late and since the hosts enjoyed costume parties in particular It was not unusual to see China's Bob Lennas With the fulcoric skirts and ribbons in their hair arriving the company of a harlequin or a cowboy That's a long first sentence. That's dog order.  Next one. I have no clue They're chauffeurs Rather than waiting outside the Toonion's house in vote. I know it had systemized systematized Mexican Gothic I wonder how you say that I love how tom is showing me the word on the page here as if I don't have a blindfold on That's a difficult one because that really has no Relation to the rest of the book. You like holding them up for them.  Nope something. Well, I have no clue. Next one way out in the white dark. Oh Oh, I know this I've done this before on the quiz. I actually don't know. I'm trying to think Oh, is it no accent? Nope. No, okay. That's sentence.  Um They don't know Um, I say thickets is a keyword thickets Thickets thickets that is a lot of trees, right? Hmm shrubbery. My mind has gone blank Three two one. Okay. Tell me what it was wilder girls wilder girls Oh, that's irritating. Okay. I've just made a massive mistake and now I'm really annoyed On the second sabbat of 12th moon in the city of weep a girl fell from the sky. Oh That one is um Muse of nightmares. No, it ain't. Oh strange strange a dreamer then. Yeah, two points though. Oh two points Rent by scooby-doo. Would you believe? Tom always says Laney Taylor reminds me of scooby-doo, but do you think she looks like Like Daphne now she looks like a character like a character from scooby-doo like a side character a side character from scooby-doo. Okay Danny Gilchrist It's a beautiful day in the city Danny Uh, no idea next one the sun is shining not a cloud in the sky The gold finch I had a great lunch in central park a chicken shawarma from the shawarma shop Which was overwhelmingly recommended to us by our listeners after last week's episode on new york city's best kept secrets So it's a podcast It's a podcast I don't think that's sadie Um Sadie Yeah, it was. Yep. Come on make some points on board now mate. I've been doing well. That was one point there. Yeah Okay, good. The scythe arrived late on a cold November afternoon side. Yeah Points on the board baby. I'll take it. It could have been other ones in the series though to be fair Do you know what I mean? So I had a one in three chance He's getting a book out Yeah, yeah, yeah Megan's library imagine being kissed about a hundred times a day I do love them cats Is it someone like I feel like someone doing a kissing boost or some shit? I don't know um No next one the tense moment just before the kiss when they look right At me like and there's no one else in the room The way they caress my cheek Maybe put their hand on the small of my back Am I comfortable? I am really uncomfortable right now and I'm feeling like I want to get up and leave um I need to make a guess You've definitely read it. I've definitely read it. No clue. Give me a second. Give me a second No, I give out.  I thought it was a imagine being kissed. I thought it was imagine being kissed No, it's I imagine being kissed. What difference does that make? Well, she's not actually being kissed I don't imagine she's imagining Yeah, but I thought she was saying to the person imagine being kissed a hundred times a day saying that happened to her So I don't think it's something different. This is how it begins. Oh, I know this but I don't This is how it begins This is I feel like I need the next sentence. Give me one more. You wake to sunlight whispering through the trees just outside the window the last nine Not the last It's a faint light weak and gray at the edges You maybe think it's it was at the last time I lied. Yeah Mary jackal stared down at her mother's coffin Strange case the apple's daughter. Yep. Come on now. Come on now. I'll give you some free points. Thank you Thank you Friday 4 45 p.m The road curves and twists unexpectedly as it leads higher and deeper into cat skill mountains As if the further you get from civilization the more uncertain the path The woods always watching no no next one the shadows are deepening the weather worsening Cat skill mountains It's not no exit No, no your last one the Hudson river is there appearing and disappearing from view This is pissing me off That's what this is It's pissing me right off What if I told you it's got it's one of those classic ones with blue and yellow font I don't remember the name of any books The sanatorium And I'm wanted guest that was the book. I was gonna I was trying to get the title I knew it was that I knew it was that when you gave me that clue and I couldn't think of what it was called I knew it was that one I couldn't think of what it was called Okay, how many points do you think you get? Okay out of 60 bearing mind three points of line one two points for line two one point for line three I'm gonna guess like 35 35 no I got 35 How do I know that? I was gonna say 36, but then I thought 35. That's not bad Yeah I thought I was quite friendly with the books I picked I picked ones I knew you'd read One You're a silly system mate. Well, thank you for helping me out. That was fun. I think I did well. I did a very good job 35 it's not bad. Thank you guys for watching. I hope you enjoyed the video If you got to the end what emoji should they comment if they got to the end? Warthog Warthog, we love the Warthog emoji. Come on the Warthog emoji, we've got to the end And see you soon in another video. Bye


Hey everyone, I'm Monica Barmbrough in the upcoming Top Gun Maverick movie. I play a fighter pilot by the name of Phoenix. While I was filming the movie, I got to meet so many incredible women. Shout out to Dragon and Bacon, as well as Jeanne and Shadi for answering thousands of questions and so so many more individuals that were just absolutely incredible. I was amazed by their professionalism, strength, courage, personal sacrifice, and it was an absolute honor to get to represent them in this film. You guys all have my respect, admiration, and appreciation, so thanks.