O the computer histy museum i hope everyone is well and fe but the pandemic we are close but the dital doors are wide open im pleased to welcome you today featuring the director of mit initiative on the Digital Economy and conversation with Pulitzer Prize winning journalist markoff. And those with the generosity under these unprecedented times we need your hp more than ever to sustain museum to dever on our mission for technology for everyone. In the future impact on humanit humanitys please continue to join and giv now to iroduce mr. Hancock to introduce todays program and speakers. I am delighted you can join todays program. And deeply influenced by social media conctions sometimes a love hate relationship and the power for od. And directorf mit initiative with Technology Writer for questions such as e aftermath of the us election and interference in 2016 and 20 what steps can we take a look at social Media Companies do on the platform without cial and with these actions we can take to have the negative effects of these in her own life so for the past two decades also worked with facebook and yahoo and snapchat among other companies with a wealth of da with the new book the hype macne. And then to argue it is not inevitable. So now well introduce the five members all scientist and engineer investors with professor of managemenat mat. And the founding partner. And the number of startups he has founded and those that have deved to protect troops and second the ranking mber and with that complication of 18 and now its goodo see you live and Technology Writer and for the New York Times and longtime friend we look forward to your conversations. I really wish we were doing thisn three dimensions instead of two but we will hang in there a little bit longer so what is it like to go on a virtual book tour . Relaxing and stressful all the same time. And then all around theorld. And as a Data Scientist and what about that she will are going from bookstore to bookstore . Its a little of both. Its more efficient in terms of the reach you dont have to travel than a lot of people like you just mentioned crave that more intimate connection and with ideas and to be in the presence of the body language. And i think we are missing and a lot of dimensions in our lives right now. But this technology has evolved more quickly so i have seen these efforts to bring the audience in. Its almost as if we want the auence and to fear that professionalism and i think we will navigate that in the weeks and the months and years to come. Kevin kelly probably has the and the best of anyone that i know use the media to promote his book it has become aestseller that has been incredibly efficiently. I will send you his press release on this it is straightforward. I see you everywhere on social media these days you are halfway the. With the social network he began as an economist. I got my phd in managerial economics undermine a phd advisor i was studying to subjects at the same time and on one hand studying traditional statistics and econometrics that all the metal on models were known as those independently distributed so all the data independent of one another and then looking at the strategy the network of the interdependence a lot of the variance in these models that assumed by the tremendous interdependence that this is more and more true than technology so in the year 2000 and to say digital social networks that i dont know anything about that and i have been studying it ever since. But what about the crossover you do this interesting work to use social networks. Yes we had a number of different collaborations over the years and we continue to collaborate. The study you are referring to was exactly that to infer networks of interaction not physical events or even in a physical space and with the longstanding work with tom allen at mat with the flow of technology and that impact of physical space and innovation and this is the modern version and those that are conferences papers on that. Tt was very interesting work. To go back and for to be a Data Scientist and entrepreneur do you get them mixed up . Thats a great question. I was the chief scientist at two startups while i was getting tenure and we were successful with a lot of work but in essence those entrepreneurial ventures flow directly so both of the startups were based in large part on scientific work tt i was doing so they go handinhand so this fantastic feedback loop so the motto of mit is hand in mind and the wing learning by doing so the classical experience of implementing these ideas in the marketplace every day also impacts my teaching so i value the feedback loop between the marketplace and the research to keep it current and relevant keeps the teaching current and relevant and vice versa. Do you ever worry but it is stanford but the idea they come and do the toe touch. That undergraduate class for six weeks. And inhose. Com phases in terms of the original role of the academy . I am a scientist entrepreneur and investor. And with a very close friend of mine the scientist entrepreneur and investor in that order. And i take it is my top priority. And that is the engine of Everything Else in that innovation and the toc work in and the lifeblood of Everything Else. And was very honored to win the award in 2018 and i take my teaching seriously. You did a good job but that made it stand out. What is a hype machine . Because the Business Model social media is based on engagement. We are living in the attention economy in the Business Model of the social platform are two and then sell that attention as advertising inventory and with those that want to promote common use and then only two countries to promote geopolitical aims. And then to hype us up. And in the short term to generate the engagement which is crucial to the Business Model. Obviously in the real world you cannot escape the red flag. It does feel like we are buried in red flags. And how they disrupt the elections are the economy and the health and that is a good summary thats where the danger lies. So democracy we should be concerned about interference and foreign interference and the spread of falsity if that is generating movements internally domestic terror movements to kidnap the governor of michigan planned over facebook and the momentum for that all the way through to Political Polarization with the algorithms on the United States and certainly the economy. So the book tells the story of the tweet put out by the ap 2013 that says barack obama was injured or killed and two explosions in the white house and the went viral. It was a real news but fake news put out by syrian hackers who hack to the ap twitter handle. And then those that were legion two other systems like trading algorithms that trade on the sentiment and they get a hold of the fake news and 140 billion of equity value and thats from a single tweet imagine we live in trillions of tweets every day small and medium and Large Enterprises and finally obviously there is a lot of coronavirus information and we track at mit the Largest Global survey and partnership with the mit additional economy in one thing were tracking and announcing pfizer last week god 90 percent on its vaccine about other vaccines but it is related to misinformation and before that it was measles. There is a lot of misinformation and vaccination in spreading and that caused a resurgence even though we had eradicated measles in the year 2000. We saw 1800 percent increase in 2019 and a lot of that is caused by the threat of misinformation. Are we talking metaphors or information affecting the biological world and information and virus is a real world now . Is definitely real world now people ask me and the first time the phrase fake news was written down in the 1930s but the difference today is the speed of breath and depth to dramatically change the nature over the last ten years and essentially created a Central Nervous system for humanity with this technology and i think thats very different than anything weve had before. What is the height loop . We wanted to go under the hood of the Tech Knowledge on technology and so one of the important things of this machine is the algorithm is the friend recommendation for the people that you may now or the news feed. To determine the structure of the human Structure Network online and that and i try to simplify this with that descriptive narrative and that height loop is a dynamic interplay with the Machine Intelligence on one hand in human agency and how we are reacting to things on what to read and then if we take those recommendations and then that feeds back into the machine side which senses what we like and what we dont like. And to understanding the height loop helps us to understand how the height machine and then with the economy or public health. And with the wisdom and the madness. And the fantastic book that was published in 2004 and the idea that crowds can make better decisions and to live at the truth faster. And the independence of the crowds opinion and the diversity of opinion and the quality of those individuals in the crowd. But the book was published in the same year Mark Zuckerberg founded facebook social media eroded all three of these principles. And what we like and abide by the confirmation bias in the two bits of science and with the relative diversity but that Experimental Evidence that shows the algorithms put some in the filter bubble that we narrow what we read and are exposed to those are different from the own and that is the definition of polarization. Now in largescale experiments with the hatred of the other party. But the way they read and think and then to bring it together is Common Ground. But then it becomes very difficult. A couple of years ago at uc berkeley ai professor. Those could be reduced at the code and how much more complicated is it actually . So with the Data Scientist mainly which is the successor the effectiveness of the Predictive Power of algorithm and then to drive these what drives the success or failure not the specificity of the equation so what that means is that this such a complex set of data on which these algorithms are operating that they are complex the granular multifaceted and multidimensional that is the nature of the complexity that we see today. And to control this polarization the fact and the spread of this information. And take these in reverse order there are a number of things that we can do. So we know largescale scientific studies have done a lot of great work that we cannot believe this information and as much and like asking people every once in a while to evaluate if a news story is true or false will get them into that reflective mode so they are less likely to believe those fake news stories and then that puts them in the reflective mood to the sharing of false news but at the same time if you do this at scale you could collect many different labels of falsity and you can see that into the Machine Learning algorithm how to label them and also you can use a growing number of employees as a human in the loop system. This and asking them what they are true or false and to implement that in Machine Learning so labeling is important to gives the providence of information and then to make better decisions. And it is extensively labeled by law. If its produced in a facility that has wheat or peanuts if you have an allergy. But the one problem with labeling is the implied truth the fact that if you start labeling things and you dont scale it quickly is the implied truth the fact that if you start labeling things and you dont scale it quickly you have to scale to be effective in a human machine and then to do you monetize fake news you cannot have ad revenue with false news. And then in search results literacy is important and institutionalize and then i have a seven yearold son and im very concerned about that and so on. That is the important first step in terms of fake news but with polarization what we found in our own experience want to turn the algorithms off so we dont become permanently change by those algorithms. So adjust the algorithms with multi various objectives the put some more weight and importance on diversity with the alternate viewpoints to help us in terms of the polarization side from a technical perspective. A facebook executive told me they limit the viral spread of all kinds of things. What about that quick. Its important i do mention this at length in the book. The study of the false news online found falsities spread further faster deeper and more broadly than the truth in every category. And doesnt ever catch up to the falsity. And that is important way to allow the truce to catch up to falsity and then to stem the coronavirus misinformation and with the election policy changes where they made it harder to retweet in the new half to and in addition before you read tweeted it. And the articles i have written and this is to slow the information down because falsity travels farther than truth. Is there any research does it have any impact . And asking you to read the reading before re tweeting it is a good first step. And with that social science should shoulder for the emergence of this machine. All of the technologist in social scientist should and do take very seriously the responsibility steering social media of the promise to the apparel many of my colleagues spent four years about these dangers and to what extent can we create a meaningful industry Academic Partnership to the point where the platforms are listening and also implementing the recommendations so the Academic Partnership for stanford and gary king at harvard and many others to get data from facebook was effect on democracy more transparent with a lot of roadblocks and the thunder threatens to pull out of social science. And then give data that was very large amounts of data. And that partnerships to work better. And then asking them to be transparent then to be ultra secure and private about the data. But at the same time to say lock everything down dont let my private data out. So they need to to be more transparent and more secure at the same time the way you can do that with technology or approach of the differential privacy to provide data in a way that is non identifiable and thats how they release so this is the essential paradox because if you remember the Cambridge Analytica a scandal began with the University Research team getting access and then passing it to Cambridge Analytica us. How do you assess the political impact of the president s twitter account . What kind of impact does it hav have . It has completely changed political discourse. This is the primary channel through which the president of the United States communicates with the world whether it is his own staff or the public and foreign leaders, et cetera this is never been the case before. It has a tremendous amount of implications to understand and how quickly it moves in some circles but not others. And the important of the platform like censoring or laboring on labeling tweets of new policies. But that is important now because the president ial communication and a lot of circumstances but then they go out at 3 00 oclock in the morning or 5 00 oclock in the morning on a whim this is an important consortium consideration Going Forward for geopolitical security for domestic security and so on and these are critical still didnt discover he had a simple password on his twitter account . It was like trump 2016 or something very simple. [laughter] so what i saw in your book President Trump has 89 million twitter followers but not all 89 million see every tweet. How do they decide who sees wha what . The algorithm behind the social media platforms rank by relevance and then tailor each feed to the individual so see the tweets in the order that is determined of an algorithm protecting what is the most relevant for you and that has a number of different features some of those might be deemed relevant and some may not. Its not a guarantee everyone sees every one of his tweets but those that they have noticed and that is true with donald trump as well. And big brother created a language called we speak and with the closure. But by limiting the size and expression with the nature of communication. And as soon as twitter came out we saw a counter idea and the idea was we will bring back longform communication in a social one social Network Style writing longer pieces and sharing them in the same way that twitter does in much shorter dialogue with the digital social network. We have an ab and flow with communication and we have a variety of tools at our disposal to communicate. And the ecosystem remains vibrant. So we dont collapse to the least common denominator and that we have multilevel communications sewer right to worry and focus on that. And with great interest with a meaningful impact on the election. Do you come down on one side or the other . And the end of reality is one chapter talks about the spread of fake news and the election and the economy and health. And whether or not it has an impact and then basically there are three takeaways from this. Does it vote choice or does it affect voter turnout and is that target with Political Campaign or misinformation and does it well targeted enough . And then the likelihood is very small most of that Scientific Evidence that persuades those messages that have very little effect they will switch from being a Hillary Clinton supporter from being a donald trump supporter whether social media or ot