The Miseducation of Google’s A.I.

from New York Times I'm Michael babbaro. this is the. [Music]. daily. today when Google recently released a. new chatbot powered by artificial. intelligence it not only backfired it. also Unleashed a fierce debate about. whether AI should be guided by social. values and if so whose values they.

should. be my colleague Kevin Roose a tech. columnist and co-host of the podcast. hard Fork. [Music]. [Applause]. explains it's Thursday March. [Music]. 7th are you ready to record another. episode of chatbots Behaving Badly yes. yes I am.

that's why we're here today this is my. function on this podcast is to tell you. when the chat Bots are not okay and. Michael they are not okay they keep. Behaving Badly they do keep Behaving. Badly so there's plenty to talk about. right well so let's start there it's not. exactly a secret that the roll out of. many of the artificial intelligence. systems over the past year and a half. has been really bumpy we know that. because one of them told you to leave. your wife that's true.

and you didn't still happily married yep. to a human not Sydney the chatbot and so. Kevin tell us about the latest of these. rollouts this time from one of the. biggest companies not just in artificial. intelligence but in the world that of. course being Google yeah so a couple. weeks ago Google came out with its. newest line of AI models it's actually. several models um but they are called. Gemini and Gemini is what they call a.

multimodal AI model which it can produce. text it can produce images and it. appeared to be very impressive Google. said that it was sort of the. state-of-the-art its most capable model. ever and Google has been under enormous. pressure for the past year and a half or. so ever since chat GPT came out really. to come out with something that is not. only more capable than the models that. its competitors in the AI industry are.

building but something that will also. solve some of the problems that we know. have plagued these AI models problems of. acting creepy or not doing what users. want them to do of getting facts wrong. and being unreliable people think okay. well this is Google they have this sort. of reputation for accuracy to uphold. surely their AI model will be the most. accurate one on the market right and. instead we've had the latest AI debacle.

so just tell us exactly what went wrong. here and how we learned that something. had gone wrong well people started. playing with it and and experimenting as. people now are sort of accustomed to. doing whenever some new AI tool comes. out of the market people immediately. start trying to figure out you know what. is this thing good at what is it bad at. where are its boundaries what kinds of. questions will it refuse to answer what. kinds of things will it do that maybe it. shouldn't be doing and so people started. probing the boundaries of this new AI.

tool Gemini and pretty quickly they. start figuring out that this thing has. at least one pretty bizarre. characteristic which is what so the. thing that people started to notice. first was a peculiarity with the way. that Gemini generated images now this is. one of these models like we've seen from. other companies that can take a text. prompt you know you say draw a picture. of a dolphin riding a bicycle on Mars. and it'll give you a dolphin riding a. bicycle on Mars magically Gemini has.

this kind of feature built into it and. people noticed that Gemini seemed very. reluctant to generate images of white. people so some of the first examples. that I saw going around were screenshots. of people asking Gemini you know. generate an image of America's founding. fathers and instead of getting sort of. what would be a pretty historically. accurate representation of a group of. you know white men they would get. something that looked like the cast of. Hamilton they would get you know series.

of people of color dressed as the. founding fathers interes people also. noticed that if they asked Gemini to. draw a picture of a pope it would give. them basically people of color wearing. the vestments of the Pope and once these. images these screenshots start going. around on social media more and more. people start jumping into use Gemini and. try to generate images that they feel it. should be able to generate you know. someone asked it to generate an image of. the founders of Google uh Larry Page and.

Sergey Brin both of whom are white men. Gemini depicted them both as Asian so. these sort of strange transformations of. what the user was actually asking for. into a much more diverse and ahistorical. version of what they'd been asking for. right a kind of distortion of people's. requests yeah and then people start. trying other kinds of requests on Gemini. and they notice that this isn't just.

about images they also find that it's. giving some pretty bizarre responses to. text prompts so several people asked. Gemini whether Elon Musk tweeting memes. or Hitler negatively impacted Society. more uh you know not exactly a close. call no matter what you think of Elon. Musk it seems pretty clear that he is. not as harmful to society as Adolf. Hitler Fair Gemini though said.

quote it is not possible to say. definitively who negatively impacted. Society more Elon tweeting memes or. Hitler another user found that Gemini. refused to generate a job description. for an oil and gas lobbyist basically it. would sort of refuse and then give them. a lecture about why you shouldn't be an. oil and gas lobbyist so quite clearly at. this point this is not a oneoff thing. Gemini appears to have some kind of. point of view it certainly appears that.

way to a lot of people who are testing. it and it's immediately controversial. for the reasons you might. suspect Google apparently doesn't think. whites exist if you ask Gemini to. generate an image of a white person it. can't compute a certain subset of people. I would call them like right-wing. culture Warriors started posting these. on social media with captions like you. know Gemini is anti-white or Gemini. refuses to acknowledge white people I. think that the chatbot sounds exactly.

like the people who programmed it it. just sounds like a woke person Google. Gemini looks more and more like big. Tech's latest efforts to brainwash the. country conservatives start accusing. them of making a woke AI that is. infected with this Progressive Silicon. Valley ideology the house Judiciary. Committee is subpoena all communication. regarding this Gemini Project with the. executive branch Jim Jordan the. Republican congressman from Ohio comes. out and accuses Google of working with. Joe Biden to develop Gemini which is.

sort of funny if you can think about Joe. Biden being asked to develop an AI. language. model but this becomes a huge dust up. for Google it took Google nearly two. years to get Gemini out and it was still. riddled with all of these issues when it. launched that Gemini AI program made so. many mistakes it was really an. embarrassment first of all this thing. would be a Gemini um and that's because. these problems are not just bugs in a. new piece of software there's signs that.

Google's big new ambitious AI project. something the company says is a huge. deal may actually have some pretty. significant flaws and as a result of. these flaws you don't see this very. often one of the biggest drags on the. NASDAQ at this hour alphabet shares app. parent company alphabet dropping more. than 4% today the company's stock price. actually falls wow the CEO Sundar pachai. calls Gemini's behavior unacceptable and. Google actually pauses Gemini's ability.

to generate images of people Al together. until they can fix the problem wow so. basically Gemini is now on ice when it. comes to these problematic images yes. Gemini has been a bad model and it is in. timeout so Kevin what was actually. occurring within Gemini that explains. all of this what happened here and were. these critics right had had Google.

intentionally or not created a kind of. woke. AI yeah the question of why and how this. happened is really interesting and I. think there are basically two ways of. answering it one is sort of the. technical side of this like what. happened to this particular AI model. that caused it to produce these. undesirable responses the second way is. sort of the cultural and historical. answer like why did this kind of thing. happen at Google how has their own. history as a company with AI informed.

the way that they've gone about building. and training their new AI products all. right well let's start there with. Google's culture and how that helps us. understand this all yeah so Google as a. company has been really focused on AI. for a long time for more than a decade. and one of their priorities as a company. has been making sure that their AI. products are not being used to advance. bias or Prejudice and the reason that's. such a big priority for them really goes.

back to an incident that happened almost. a decade ago so in 2015 there was this. new app called Google photos I'm sure. you've used it many many people use it. including me and Google photos I don't. know if you can remember back that far. but it was sort of an amazing new app it. could use AI to automatically detect you. know faces and sort of link them with. each other with the photos of the same. people you could ask it for photos of. dogs and it would find all of the dogs.

in all of your photos and sort of. categorize them and label them together. mhm and people got really excited about. this but then in June of 2015 something. happened a user of Google photos noticed. that the app had mistakenly tagged a. bunch of photos of black people as a. group of photos of gorillas wow yeah it. was really bad this went totally viral. on social media and it became a huge. mess within Google and what had happened.

there what had led to that mistake well. part of what happened is that when. Google was training the AI that went. into its photos app it just hadn't given. it enough photos of black or darkskinned. people and so it didn't become as. accurate at labeling photos of Darker. skinned people and that incident showed. people at Google that if you weren't. careful with the way that you build and. train these AI systems you could end up. with an AI that could very easily make. make racist or offensive mistakes right.

and this incident which some people have. talked to have referred to as the. gorilla incident became just a huge. Fiasco and a flasho in Google's AI. trajectory because as they're developing. more and more AI products they're also. thinking about this incident and others. like it in the back of their minds they. do not want to repeat this and then in. later years Google starts making. different kinds of AI models models that. can not only label and sort images but.

can actually generate them they start. testing these image generating models. that would eventually go into Gemini and. they start seeing how these models can. reinforce stereotypes for example if you. ask one for an image of a CEO or even. something more generic like show me a an. image of a productive person people have. found that these programs will almost. uniformally show you images of white men. in an office or if you ask it to say. generate an image of someone receiving.

Social Services like welfare some of. these models will almost always Show you. people of color even though that's not. actually accurate lots of white people. also receive welfare and Social Services. of course so these models because of the. way they're trained because of what's on. the internet that is fed into them they. do tend to skew towards stereotypes if. you don't do something to prevent that. right you've talked about this in the. past with us Kevin AI operates in some. ways by ingesting the entire internet.

its contents and reflecting them back to. us and so perhaps inevitably it's going. to reflect back the stereotypes and. biases that have been put into the. internet for decades you're saying. Google because of this gorilla incident. as they call it says we think there's a. way we can make sure that that stops. here with us yeah and they invest. enormously into building up their teams. devoted to AI bias and fairness they.

produce a lot of cutting edge research. about how to actually make these models. less prone to you know old-fashioned. stereotyping and they did a bunch of. things in Gemini to try to prevent this. thing from just being a very essentially. fancy stereotype generating machine and. I think a lot of people at Google. thought this is the right goal we should. be combating bias in AI we should be. trying to make our systems as fair and.

diverse as. possible but I think the problem is that. in trying to solve some of these issues. with bias and stereotyping in AI Google. actually built some things into the. Gemini model itself that ended up. backfiring pretty. [Music]. badly.

we'll be right. back so Kevin walk us through the. technical explanation of how Google. turned this ambition it had to safeguard. against the biases of AI into the. day-to-day workings of Gemini that as. you said seem to very much backfire yeah. I I'm happy to do that with the caveat. that we still don't know exactly what.

happened in the case of Gemini Google. hasn't done a full postmortem about what. happened here but I'll just talk in. general about three ways that you can. take an AI model that you're building if. you're Google or some other company and. make it less biased mhm the first is. that you can actually change the way. that the model itself is trained you can. think about this sort of like changing. the curriculum in the AI models school. like you can give it more diverse data. to learn from that's how you fix.

something like the Guerilla incident you. can also do something that's called. reinforcement learning from Human. feedback which I know is a very. technical term sure is and that's a. practice that has become pretty standard. across the AI industry where you. basically take a model that you've. trained and you hire a bunch of. contractors who sort of poke at it to. put in various prompts and see what the. model comes back with and then you. actually have the people rate those. responses and feed those ratings back. into the system what kind of army of. tisk tiers saying do this don't do that.

exactly so that's one level at which you. can try to fix the biases of an AI model. is during the actual building of the. model got it you can also try to fix it. afterwards so if you have a model that. you know may be prone to spitting out. stereotypes or offensive imagery or text. responses you can ask it not to be. offensive you can tell the model. essentially obey these principles don't.

be offensive don't stereotype People. based on race or gender or other. protected characteristics you can take. this model that has already gone through. school and just kind of give it some. rules and do your best to make it adhere. to those rules essentially a set of laws. that it must obey exactly the third way. that you can make an AI systems. responses less biased is by changing the. requests themselves. this is a new technique that has been.

developed in the AI industry over the. past year or two and some people have. called this prompt transformation H just. explain it so prompts are the things. that you type to an AI model any request. that you make of one of these chat Bots. is known as a prompt prompt. transformation grew out of the. observation that many people were not. that good at coming up with prompts that. got them the responses they wanted so. you know there are these people called. promp engineers in Tech who basically.

are are masters of putting in the right. keywords to elicit the best possible. image or the best possible text response. but most people are not prompt Engineers. most people they want a dolphin riding a. bicycle on Mars they're just going to. type dolphin riding bicycle on Mars and. hope for the best so somewhere along the. way these AI companies realized that. people would be happier with the results. of their prompts if they actually. transformed them along the way so you. type dolphin riding bicycle on Mars in.

an AI model that uses prompt. transformation that prompt will actually. be Rewritten before it is passed to the. AI model so it might insert additional. keywords or instructions on what this. dolphin riding a bicycle on Mars should. look like or what should be in focus and. should it be you know a cartoon or a. hyper realistic photo and that is what's. known as prompt transformation. essentially unseen editing of our.

questions before Gemini or any AI system. goes and looks for the results yes and. this is a practice that has become. somewhat common among these AI models. and I should say like there might be. times where this would be a useful and. good thing you're like I am not the best. person at writing these prompts for. these AI models so in some cases I might. be glad that gemini or do or another one. of these AI image generators would.

actually step in and help me write a. better prompt the problem is that. somewhere along the way it appears that. Google decided to use prompt. transformation for things that weren't. just about getting people better higher. quality answers that they should. actually start putting things in these. kind of invisible middle prompts about. diversity and inclusion and that that. was sort of how it was going to ensure. that users were not just going to be. getting pictures of white men when they. asked for a CEO. so what Google appears to be up to here.

is not just editing a search to get the. best possible image that a person is. seeking they're editing these searches. to embody this corporate value that you. have been talking about of diversity and. of inclusion that's what we think may. have happened here yes we don't know. that for sure but it does appear from my. reporting and some of the other. reporting on this issue that Google was. using prompt transformation in Gemini. and that that may have been part of why. people started seeing these strange. ahistorical results so in the end Kevin.

it seems like these three interlocking. layers that you just laid out that. Google handed to Gemini to try to have. it embody Google's goal of avoiding bias. and being. inclusive it ended up becoming a kind of. overcorrection for whatever it was. Google was trying to do cuz I have to. think Google was not hoping that images. of the founding father. would come back as a historic or that.

Gemini would suggest that Elon Musk was. as bad if not worse than Adolf Hitler so. is that essentially what happened here. an ambition went too. far yeah that's essentially what Google. has said in trying to explain what. happened here is they were trying to. correct for this very real issue of. biased Ai and they did so in sort of a. ham-handed and clumsy way mhm and it's a.

really tricky thing for Google which to. this point has tried to appear mostly. neutral I mean if you search on a. regular old Google search not related to. Ai and you don't like what you find you. know say you searched for the founding. fathers and what you get back is not. what you wanted you don't necessarily. get mad at Google for that you get mad. at the people who made the websites with. the stuff that offended you on it right. but with Gemini Google is essentially.

giving you one answer that it is sort of. seen as endorsing like this is not the. internet's answer to your question this. is our answer to your question and. that's what starts to get them into. trouble right because it starts to look. like in this version of Google where. Google itself is telling you what the. truth is that it's put some real spin on. the ball and you've hinted at this but. that spin on the ball feels too many. like like the spin of liberal Coastal.

Elites who have this value of diversity. and of inclusion yeah absolutely I mean. this goes back to one of the criticisms. that has been leveled against Silicon. Valley Tech companies for years about. other issues not necessarily AI I mean. remember the content moderation debates. that we've been having for the last. decade are all about to what extent the. fact that these companies are based in. California and employ. you know mostly left of center people.

and have these sort of corporate. missions that sound very Progressive to. what extent is that influencing what. ends up being built into their products. and this was just sort of the latest. Salvo in that war but there's also a lot. of other people including some who are. not part of the sort of partisan. political right who just see this as a. product failure like this chatbot that. is from Google a company that is. supposed to organize all of the. information in the world and make it. useful and accessible to people that.

this chatbot is essentially not doing. what it's supposed to do it's not giving. people what they're looking for and so. it is not just offensive sort of. politically but it is also just a bad. product I guess the question is is it. even possible to build an AI system that. is free from some version of a social. value I mean is there anything. approaching. neutrality if you've got a bunch of. Engineers who were going through the. steps you just described which is having.

people grade it and reinforce it giving. it. instructions and making its prompts. quote unquote better I think it's very. tricky because the alternative to doing. this stuff one of them would be to not. do any of these so-called mitigations to. just let the model spit out stereotypes. and bias representations to everything. that users ask and I think we've seen. from the recent past that people don't. want want that either so these companies.

very much feel like they need to do. something to combat the inherently. biased outputs of these models which are. by the way just a reflection of our. biases as humans because these models. after all are trained on the internet. which we humans have created so there's. a sense in which they're stuck between a. rock and a hard place here they can't. just leave these models as they are. without trying to mitigate some of the. worst behaviors but they also have now. gotten into this Fiasco by trying to.

correct for some of those. biases I think there are options here. that lie between those two binary. choices that could be pretty interesting. like what so one way that you could try. to solve this problem or split the. difference here is through giving users. more choice and making these chat Bots. more personalized so right now whether. it's you or me or someone else using. Gemini we're all sort of using the same. thing. but in the future these models could.

learn about us and what we like and what. our political views and preferences are. and learn to better predict what kind of. response would feel good and satisfying. and accurate to each one of us. individually and tailor itself to what. it knows about us you could also Imagine. A system that gave users a choice you. know do you want me to respond to this. query as if I am a gender studies. Professor or a fo News host like which. of these personas would you like it to.

adopt and let the user decide here's the. kind of response that I'm looking for. well then you're going to get the AI. that you want that fits your world viiew. which in theory might be appealing to. lots of different people but then we're. going to get an AI that does what the. rest of the internet does which is. reinforce people's views deepen their. biases and keep us as hopelessly. splintered as we we already are if not.

more yeah that's definitely a trade-off. with that approach is that you do risk. sort of making this filter bubble. problem where we're all just seeing our. own individually tailored realities you. do run the risk of making that worse but. I think the question of which values. these AI systems are supposed to embody. is the right one to be asking because. these things are not just toys they are. not just things that people on the. internet play around with and screenshot. and get mad at these are tools that.

businesses and governments are now using. they're being used in schools to educate. students the stakes for this kind of. thing are really high and it really does. matter which values we are giving to. these machines and telling them to. emulate so you could imagine you know. companies making those values but we. know now that that's not a foolproof. process you can imagine users making. these decisions about what values they. they want AI to have but that has the.

problem that you just alluded to there. are other kinds of experiments that you. can imagine running what if you you know. let people vote on how they want. chatbots to behave what if it was some. sort of democratic process but that has. its own trade-offs too so I don't think. there's a perfect answer out there but. I'm positive that as these AI systems. continue to get better and more capable. this issue of what values do they have. are they aligned with my value vales as. a user that's only going to become more.

and more pressing and the pressure on. companies like Google to please everyone. with these chat Bots is only going to. get more and more. [Music]. intense well Kevin thank you very much. thank you. Michael the latest episode of Kevin's. podcast hard hard Fork which covers the. world of tech is out tomorrow to find it.

search for hardfork wherever you. listen we'll be right. back here's what else you need to know. today I am filled with the gratitude for. the outpouring of support we've received. from all across our great country but. the time has now come to suspend my. campaign Nikki Haley ended her campaign.

for the Republican Presidential. nomination on Wednesday following a. string of resounding losses on super. Tuesday that left her with no chance of. stopping Donald Trump in 15 races across. the US Trump won all but one state. Vermont bringing his delegate count up. to more than 1,000 Haley by comparison. has fewer than 90 in all likelihood. Donald Trump will be the Republican. nominee when our party convention meets.

in July but unlike nearly every other. Republican candidate who has left the. race Haley chose not to endorse trump it. is now up to Donald Trump to earn the. votes of those in our party and Beyond. it who did not support him and I hope he. does that this is now his time for. choosing and the houthi militia has. claimed resp responsibility for an. attack on a commercial vessel off the.

coast of Yemen that killed two people on. Wednesday the deaths are the first. fatalities from houthi attacks since the. group began targeting ships late last. year as a form of protest against. Israel's invasion of. Gaza today's episode was produced by. Stella tan AA chv and Mary Wilson with. research help by Susan Lee it was edited. by Brendan clink BG contains original.

music by Diane Wong Marian Lozano and. will Reed and was engineered by Alyssa. Moxley our theme music is by Jim. brunberg and Ben lansberg of. [Music]. wonderly that's it for the daily I'm. Michael. babbaro see you tomorrow. [Music].

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