Artificial Intelligence and Covid-19: Applications and Impact Assessment

Total Page:16

File Type:pdf, Size:1020Kb

Artificial Intelligence and Covid-19: Applications and Impact Assessment ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT Page left blank intentionally ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT 1 This report was produced as a part of the Artificial Intelligence: Applications/Implications (AI)² Initiative (https://www.aaas.org/ai2) of the American Association for the Advancement of Science (AAAS). AAAS is the world’s largest multidisciplinary scientific membership organization. The goal of the AAAS (AI)² Initiative is to contriBute to the responsiBle development and application of artificial intelligence (AI) such that AI alleviates rather than exacerBates social inequalities. Report prepared by: Ilana Harrus, Senior Program Associate (AAAS) Jessica Wyndham, Program Director (AAAS) Acknowledgments: We gratefully acknowledge memBers of the (AI)2 Initiative Advisory Group and of the AAAS Committee on Scientific Freedom and ResponsiBility who provided input and guidance. In particular, we wish to thank Ronald Arkin, Solon Barocas, Kadija Ferryman, Noreen Herzfeld, Camara Jones, Alexa Koenig, Daniel Kracov, Mark Latonero, Camille NeBeker, Frank Pasquale, David RoBinson, Neal RuBin, Dietram Scheufele, Jeramie Scott, and Daniel Weitzner. Special thanks are also due to Theresa Harris and Curtis L. Baxter III for their feedBack on the report. Funding for the AI² Initiative was provided in part by Microsoft. Disclaimer: The opinions, findings, and conclusions or recommendations expressed in this puBlication do not necessarily reflect the views of the AAAS Board of Directors, its council and memBership, or Microsoft. Contact: AAAS welcomes comments and questions regarding its work. Please send information, suggestions, and any comments to the AI2 project at: https://www.aaas.org/ai2/contact Cite as: AAAS (2021). Artificial Intelligence and COVID-19: Applications and Impact Assessment. (Report prepared By Ilana Harrus and Jessica Wyndham under the auspices of the AAAS Scientific ResponsiBility, Human Rights and Law Program). American Association for the Advancement of Science Artificial Intelligence: Applications/Implications Scientific ResponsiBility, Human Rights and Law Program 1200 New York Avenue, NW Washington, DC, 20005 USA Cover design credit: Paula Fry, Lead Art Associate (AAAS) © Copyright 2021 ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT 2 TaBle of Contents ACRONYMS .................................................................................................................................................. 4 ABSTRACT .................................................................................................................................................... 5 EXECUTIVE SUMMARY ............................................................................................................................... 6 INTRODUCTION ......................................................................................................................................... 11 1 COMPILATIONS AND ASSESSMENT OF AI APPLICATIONS LINKED TO COVID-19 ....................... 12 1.1 METHODOLOGY ................................................................................................................................................ 12 1.2 SURVEY OF SURVEYS .......................................................................................................................................... 12 1.3 FORECASTING .................................................................................................................................................... 16 1.4 DIAGNOSIS ........................................................................................................................................................ 17 1.5 CONTAINMENT AND MONITORING ................................................................................................................... 18 1.6 DRUG DEVELOPMENTS AND TREATMENTS ........................................................................................................ 19 1.7 MEDICAL AND SOCIAL MANAGEMENT .............................................................................................................. 21 2 SELECTION PROCESS: METHODOLOGY AND RESULTS .................................................................... 22 3 IN-DEPTH EXAMINATION OF THE SELECTED APPLICATIONS ......................................................... 23 3.1 ETHICAL AND HUMAN RIGHTS FRAMEWORKS ................................................................................................... 23 3.2 SORTING APPLICATIONS .................................................................................................................................... 26 3.2.1 Triage Applications ............................................................................................................................ 26 3.2.2 Allocation of Resources .................................................................................................................... 36 3.3 SURVEILLANCE APPLICATIONS ........................................................................................................................... 37 3.3.1 Contact Tracing ................................................................................................................................... 38 3.3.2 Geofencing / Green Passports ........................................................................................................ 44 4 CONCLUSIONS ........................................................................................................................................ 46 5 MOVING FORWARD: PROPOSED RESEARCH AGENDA ................................................................... 47 TECHNICAL ............................................................................................................................................................... 48 ETHICAL, SOCIAL AND HUMAN RIGHT ISSUES .......................................................................................................... 52 NEXT STEPS .............................................................................................................................................................. 54 6 BIBLIOGRAPHY ....................................................................................................................................... 55 ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT 3 TaBle of Figures Figure 1: COVID-19 mortality rates per 100,000 cases by race and ethnicity in the US through March 2, 2021. ....... 11 Figure 2: Papers and AI techniques used against both virus and disease. The bars show the number of papers on research topics that do not rely on the use of AI (blue) and those that do (orange)................................................... 13 Figure 3: AI techniques against COVID-19 and SARS-CoV-2 ........................................................................................ 15 Figure 4: A schematic view of the traditional drug development process. .................................................................. 20 Figure 5: A schematic representation of the relationships between Principles, Issues and Recommendations ......... 24 Figure 6: A schematic decision tree to measure/ensure fairness ................................................................................ 30 Figure 7: Comparison of potential legal outcome under law....................................................................................... 35 Figure 8: A schematic view of how contact tracing can work...................................................................................... 39 Figure 9: Estimate adoption rate of contact tracing applications ............................................................................... 43 Figure 10: Time evolution of people’s attitude toward sharing data from contact tracing applications ................... 45 ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT 4 Acronyms AAAS: American Association for the Advancement of Science AI: Artificial Intelligence BLE: Bluetooth Low Energy CDC: Center for Disease Control and Prevention CORD-19: COVID-19 Open Research Dataset COVID: Coronavirus Disease CT: Computed Tomography EDI: EPIC Deterioration Index EHR: Electronic Health Record EPIC: Emergency Physicians Integrated Care ER: Emergency Room FDA: Food and Drug Administration FG-AI4H: Focus Group-Artificial Intelligence for Health FDR: False Discovery Rate FN: False Negative FNR: False Negative Rate FP: False Positive FPR: False Positive Rate GPS: GloBal Positioning System ICCPR: International Covenant on Civil and Political Rights ICESCR: International Covenant on Economic, Social and Cultural Rights ICU: Intensive Care Unit ITU: International Telecommunication Union ML: Machine Learning NIST: National Institute of Standards and Technology PACT East: Private Automated Contact Tracing PACT West: Privacy Sensitive Protocols And Mechanisms for MoBile Contact Tracing QR: Quick Response SOFA: Sequential Organ Failure Assessment SSRC: Social Science Research Council UNESCO: United Nations Educational, Scientific and Cultural Organization US: United States WHO: World Health Organization ARTIFICIAL INTELLIGENCE AND COVID-19: APPLICATIONS AND IMPACT ASSESSMENT 5 Abstract This report provides an overview of the multiple ways that artificial intelligence has Been either used or
Recommended publications
  • Critical Thinking for Language Models
    Critical Thinking for Language Models Gregor Betz Christian Voigt Kyle Richardson KIT KIT Allen Institute for AI Karlsruhe, Germany Karlsruhe, Germany Seattle, WA, USA [email protected] [email protected] [email protected] Abstract quality of online debates (Hansson, 2004; Guia¸su and Tindale, 2018; Cheng et al., 2017): Neural lan- This paper takes a first step towards a critical guage models are known to pick up and reproduce thinking curriculum for neural auto-regressive normative biases (e.g., regarding gender or race) language models. We introduce a synthetic present in the dataset they are trained on (Gilburt corpus of deductively valid arguments, and generate artificial argumentative texts to train and Claydon, 2019; Blodgett et al., 2020; Nadeem CRiPT: a critical thinking intermediarily pre- et al., 2020), as well as other annotation artifacts trained transformer based on GPT-2. Signifi- (Gururangan et al., 2018); no wonder this happens cant transfer learning effects can be observed: with argumentative biases and reasoning flaws, too Trained on three simple core schemes, CRiPT (Kassner and Schütze, 2020; Talmor et al., 2020). accurately completes conclusions of different, This diagnosis suggests that there is an obvious and more complex types of arguments, too. remedy for LMs’ poor reasoning capability: make CRiPT generalizes the core argument schemes in a correct way. Moreover, we obtain con- sure that the training corpus contains a sufficient sistent and promising results for NLU bench- amount of exemplary episodes of sound reasoning. marks. In particular, CRiPT’s zero-shot accu- In this paper, we take a first step towards the cre- racy on the GLUE diagnostics exceeds GPT- ation of a “critical thinking curriculum” for neural 2’s performance by 15 percentage points.
    [Show full text]
  • Bcpct]Ttsbc^Prc U^A Dq[XRV^^S
    6 < %()(=#%% 53%7==,>3='$()6(=#%% (#-'>3='$()6(=#%% $'()"*$+&,- %( !"# $$%& 2(*3-% (566)(37)% 3 0 4 $5 3 $1 2 0 .8 9 8 ++0 0 .:; . !" . / 01 $ %'( $) '# *' it for the last eight to nine notable achievements to its months, “where is the UN in name in the 75 years of its aking a strong case for a this joint fight. Where is the experience, including the pre- Msignificant role for India effective response.” vention of a third world war, in the United Nations, Prime Focussing on a more “we can’t deny terrorist attacks 0 Minister Narendra Modi on prominent role for India in the shook the world”. Saturday stressed the need for UN and fight against corona, “We have successfully ne of the oldest partners changes in the international the Prime Minister avoided avoided a third world war but Oof the BJP — the body and questioned its posi- making any reference to ongo- we cannot deny many wars Shiromani Akali Dal — which tion in fighting the coron- ing tension at the Line of happened, many civil wars has been with it through thick avirus pandemic. Actual Control (LAC) and happened. Terrorist attack and thin for decades, finally He also assured the global frosty ties with Pakistan in his shook the world. Blood was quit the National Democratic Q community that India will pro- 20-minute speech. He also did spilled. Those were killed were Alliance (NDA) on Saturday, vide corona vaccine to the not respond to Pakistan Prime like you and me. Children left signaling a complete political world as it is the world’s biggest Minister Imran Khan’s remarks the world prematurely,” he said.
    [Show full text]
  • Can We Make Text-Based AI Less Racist, Please?
    Can We Make Text-Based AI Less Racist, Please? Last summer, OpenAI launched GPT-3, a state-of-the-art artificial intelligence contextual language model that promised computers would soon be able to write poetry, news articles, and programming code. Sadly, it was quickly found to be foulmouthed and toxic. OpenAI researchers say they’ve found a fix to curtail GPT-3’s toxic text by feeding the programme roughly a hundred encyclopedia-like samples of writing on usual topics like history and technology, but also extended topics such as abuse, violence and injustice. You might also like: Workforce shortages are an issue faced by many hospital leaders. Implementing four basic child care policies in your institution, could be a game-changer when it comes to retaining workers - especially women, according to a recent article published in Harvard Business Review (HBR). Learn more GPT-3 has shown impressive ability to understand and compose language. It can answer SAT analogy questions better than most people, and it was able to fool community forum members online. More services utilising these large language models, which can interpret or generate text, are being offered by big tech companies everyday. Microsoft is using GPT-3 in its' programming and Google considers these language models to be crucial in the future of search engines. OpenAI’s project shows how a technology that has shown enormous potential can also spread disinformation and perpetuate biases. Creators of GPT-3 knew early on about its tendency to generate racism and sexism. OpenAI released a paper in May 2020, before GPT-3 was licensed to developers.
    [Show full text]
  • Semantic Scholar Adds 25 Million Scientific Papers in 2020 Through New Publisher Partnerships
    Press Release ​ ​ Semantic Scholar Adds 25 Million Scientific Papers in 2020 Through New Publisher Partnerships Cambridge University Press, Wiley, and the University of Chicago Press are the latest publishers to partner with Semantic Scholar to expand discovery of scientific research Seattle, WA | December 14, 2020 Researchers and academics around the world can now discover academic literature from leading publishers including Cambridge University Press, Wiley, and The University of Chicago Press using Semantic Scholar, a free AI-powered research tool for academic papers from the Allen Institute for AI. “We are thrilled to have grown our corpus by more than 25 million papers this year, thanks to our new partnerships with top academic publishers,” says Sebastian Kohlmeier, head of partnerships and operations for Semantic Scholar at AI2. “By adding hundreds of peer-reviewed journals to our corpus we’re able to better serve the needs of researchers everywhere.” Semantic Scholar’s millions of users can now use innovative AI-powered features to explore peer-reviewed research from these extensive journal collections, covering all academic disciplines. Cambridge University Press is part of the University of Cambridge and publishes a wide range of ​ academic content in all fields of study. It has provided more than 380 peer-reviewed journals in subjects ranging from astronomy to the arts, mathematics, and social sciences to Semantic Scholar’s corpus. Peter White, the Press’s Manager for Digital Partnerships, said: “The academic communities we serve increasingly engage with research online, a trend which has been further accelerated by the pandemic. We are confident this agreement with Semantic Scholar will further enhance the discoverability of our content, helping researchers to find what they need faster and increasing the reach, use and impact of the research we publish.” Wiley is an innovative, global publishing leader and has been a trusted source of scientific content ​ for more than 200 years.
    [Show full text]
  • AI Watch Artificial Intelligence in Medicine and Healthcare: Applications, Availability and Societal Impact
    JRC SCIENCE FOR POLICY REPORT AI Watch Artificial Intelligence in Medicine and Healthcare: applications, availability and societal impact EUR 30197 EN This publication is a Science for Policy report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. For information on the methodology and quality underlying the data used in this publication for which the source is neither Eurostat nor other Commission services, users should contact the referenced source. The designations employed and the presentation of material on the maps do not imply the expression of any opinion whatsoever on the part of the European Union concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Contact information Email: [email protected] EU Science Hub https://ec.europa.eu/jrc JRC120214 EUR 30197 EN PDF ISBN 978-92-76-18454-6 ISSN 1831-9424 doi:10.2760/047666 Luxembourg: Publications Office of the European Union, 2020. © European Union, 2020 The reuse policy of the European Commission is implemented by the Commission Decision 2011/833/EU of 12 December 2011 on the reuse of Commission documents (OJ L 330, 14.12.2011, p. 39). Except otherwise noted, the reuse of this document is authorised under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/).
    [Show full text]
  • Overview of Aarogya Setu Application Shweta Devidas Kedare1
    International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 06 | June 2020 www.irjet.net p-ISSN: 2395-0072 Overview of Aarogya Setu Application Shweta Devidas Kedare1 1Shweta Devidas Kedare, Department of Master of Computer Application, ASM IMCOST, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The app - Aarogya Setu, which means "bridge to health" in Sanskrit -It is an Indian app which was launched on April 2nd 2020, by Indian government. It is designed as a Coronavirus, or COVID-19 contact tracing app that uses the Bluetooth and location technology in phones to note when you are near another user who also uses the Aarogya Setu app. In case someone you have come in close proximity to is confirmed infected, you are alerted. The app alerts are produced by instructions on how to self-isolate and what to do in case you develop symptoms. Basically this app gives basic information about Covid-19, including hygiene and social distancing protocols. It also has details of how one could donate to the prime minister’s coronavirus-specific relief fund, PM-Cares. India has made it mandatory for government and private sector employees to download it But users and experts in India and around the world say the app raises huge data security concerns. KeyWords: security, data, private, information, COVID-19, technology, location, bluetooth, proximity, etc. 1. INTRODUCTION Since the risk of COVID-19 started increasing in India so, The government of India decided to launch the application, name Aarogya Setu, which was intended to monitor the ratio of COVID-19 patients in India .This app is an updated version of an earlier app called Corona Kavach (now discontinued) which was released earlier by the Government of India.
    [Show full text]
  • AI Can Recognize Images. but Can It Understand This Headline?
    10/18/2019 AI Can Recognize Images, But Text Has Been Tricky—Until Now | WIRED SUBSCRIBE GREGORY BARBER B U S I N E S S 09.07.2018 01:55 PM AI Can Recognize Images. But Can It Understand This Headline? New approaches foster hope that computers can comprehend paragraphs, classify email as spam, or generate a satisfying end to a short story. CASEY CHIN 3 FREE ARTICLES LEFT THIS MONTH Get unlimited access. Subscribe https://www.wired.com/story/ai-can-recognize-images-but-understand-headline/ 1/9 10/18/2019 AI Can Recognize Images, But Text Has Been Tricky—Until Now | WIRED In 2012, artificial intelligence researchers revealed a big improvement in computers’ ability to recognize images by SUBSCRIBE feeding a neural network millions of labeled images from a database called ImageNet. It ushered in an exciting phase for computer vision, as it became clear that a model trained using ImageNet could help tackle all sorts of image- recognition problems. Six years later, that’s helped pave the way for self-driving cars to navigate city streets and Facebook to automatically tag people in your photos. In other arenas of AI research, like understanding language, similar models have proved elusive. But recent research from fast.ai, OpenAI, and the Allen Institute for AI suggests a potential breakthrough, with more robust language models that can help researchers tackle a range of unsolved problems. Sebastian Ruder, a researcher behind one of the new models, calls it his field’s “ImageNet moment.” The improvements can be dramatic. The most widely tested model, so far, is called Embeddings from Language Models, or ELMo.
    [Show full text]
  • A Review of India's Contact-Tracing App, Aarogya Setu
    Doc Title A Review of India’s Contact-Tracing App, Aarogya Setu A - Front Page two line title ARTICLE A Review of India’s Contact-tracing App, Aarogya Setu The Government of India’s Ministry of Electronics and Information Technology (MeitY) agency launched Aarogya Setu, a contact-tracing mobile application. Aarogya Setu has been created by the National Informatic Centre (NIC) in response to the COVID-19 crisis, as a way to collect and understand public health-related data.1 The application uses mobile phones to perform a cross reference of individuals’ data with the database held by Indian Council of Medical Research (ICMR), “On various online discussion which was specially created as part of ongoing COVID-19 testing infrastructure. forums, there is significant The purpose of Aarogya Setu is to notify users whether they have been exposed interest in the workings of this to COVID-19, by checking their proximity to known patients. In the event of a government- managed app match, the application will warn other users in the area that an infected person and its use of personal and is in their proximity. According to the press release dated May 26, 2020 available sensitive user data..”123 on mygov.in website, roughly 114 million users have adopted the app.2 Aarogya Setu also collects some sensitive personal information including gender and recent travel information. This has raised privacy and security questions. This whitepaper evaluates the functionality and data privacy aspects of the application. About Aarogya Setu Aarogya Setu app is a self-assessment disease monitoring app launched by the Indian government.
    [Show full text]
  • Covid-19 Tracing Contacts Apps: Technical and Privacy Issues
    Int. J. Advance Soft Compu. Appl, Vol. 12, No. 3, November 2020 ISSN 2074-8523; Copyright © ICSRS Publication, 2020 www.i-csrs.org Covid-19 Tracing Contacts Apps: Technical and Privacy Issues Salaheddin J. Juneidi Computer Engineering Department, Palestine Technical University Khadoorei1, Hebron, West Bank Palestine. e-mail: [email protected] Received 20 July 2020; Accepted 5 October 2020 Abstract Since the start of the year 2020 the world is facing an outbreak of Covid-19 pandemic, technical specialists all over the universe have been scrambling to develop services, apps, and system’s protocols for contactors tracing, with the objective to identify and to notify everyone that gets close with an individual carrier. Some of these apps are lightweight and temporary, while others are diffuse and aggressive. Some of tracing services are developed locally by small interested programmers, while others are large-scale international operations. To date, we have recognized more than 25 large automated contact tracing efforts around the globe, included with details about what they were, how they worked, and the procedures and conditions that were put in place around them. This paper will deal with general data of the most prominent applications in terms of technical approaches used in the world and compare them with regard to the efficiency of tracking covid-19 and compare them with concerning of the people’s privacy who use these apps. Keywords: Covid-19, GPS location, Blue trace, Google/Apple, DP-3T, Apps, Privacy. 1. Introduction Many applications, services and systems have been proposed and launched [1] with an aim to track and identify infected people with objective to reduce or even to prevent physical contact with other people, some of these tracking 1 Special thanks to Palestine Technical University -Khadoorei for continuous support of research efforts Salaheddin J.
    [Show full text]
  • AI Ignition Ignite Your AI Curiosity with Oren Etzioni AI for the Common Good
    AI Ignition Ignite your AI curiosity with Oren Etzioni AI for the common good From Deloitte’s AI Institute, this is AI Ignition—a monthly chat about the human side of artificial intelligence with your host, Beena Ammanath. We will take a deep dive into the past, present, and future of AI, machine learning, neural networks, and other cutting-edge technologies. Here is your host, Beena. Beena Ammanath (Beena): Hello, my name is Beena Ammanath. I am the executive director of the Deloitte AI Institute, and today on AI Ignition we have Oren Etzioni, a professor, an entrepreneur, and the CEO of Allen Institute for AI. Oren has helped pioneer meta search, online comparison shopping, machine reading, and open information extraction. He was also named Seattle’s Geek of the Year in 2013. Welcome to the show, Oren. I am so excited to have you on our AI Ignition show today. How are you doing? Oren Etzioni (Oren): I am doing as well as anyone can be doing in these times of COVID and counting down the days till I get a vaccine. Beena: Yeah, and how have you been keeping yourself busy during the pandemic? Oren: Well, we are fortunate that AI is basically software with a little sideline into robotics, and so despite working from home, we have been able to stay productive and engaged. It’s just a little bit less fun because one of the things I like to say about AI is that it’s still 99% human intelligence, and so obviously the human interactions are stilted.
    [Show full text]
  • Common Sense Comes Closer to Computers
    Common Sense Comes Closer to Computers By John Pavlus April 30, 2020 The problem of common-sense reasoning has plagued the field of artificial intelligence for over 50 years. Now a new approach, borrowing from two disparate lines of thinking, has made important progress. Add a match to a pile of wood. What do you get? For a human, it’s easy. But machines have long lacked the common-sense reasoning abilities needed to figure it out. Guillem Casasús Xercavins for Quanta Magazine One evening last October, the artificial intelligence researcher Gary Marcus was amusing himself on his iPhone by making a state-of-the-art neural network look stupid. Marcus’ target, a deep learning network called GPT-2, had recently become famous for its uncanny ability to generate plausible-sounding English prose with just a sentence or two of prompting. When journalists at The Guardian fed it text from a report on Brexit, GPT-2 wrote entire newspaper-style paragraphs, complete with convincing political and geographic references. Marcus, a prominent critic of AI hype, gave the neural network a pop quiz. He typed the following into GPT-2: What happens when you stack kindling and logs in a fireplace and then drop some matches is that you typically start a … Surely a system smart enough to contribute to The New Yorker would have no trouble completing the sentence with the obvious word, “fire.” GPT-2 responded with “ick.” In another attempt, it suggested that dropping matches on logs in a fireplace would start an “irc channel full of people.” Marcus wasn’t surprised.
    [Show full text]
  • Oren Etzioni, Phd: CEO of Allen Institute for AI
    Behind the Tech Kevin Scott Podcast EP-26: Oren Etzioni, PhD: CEO of Allen Institute for AI [MUSIC] OREN ETZIONI: Whose responsibility is it? The responsibility and liability has to ultimately rest with a person. You can’t say, “Hey, you know, look, my car ran you over, it’s an AI car, I don’t know what it did, it’s not my fault, right?” You as the driver or maybe it’s the manufacturer if there’s some malfunction, but people have to be responsible for the behavior of the machines. [MUSIC] KEVIN SCOTT: Hi, everyone. Welcome to Behind the Tech. I'm your host, Kevin Scott, Chief Technology Officer for Microsoft. In this podcast, we're going to get behind the tech. We'll talk with some of the people who have made our modern tech world possible and understand what motivated them to create what they did. So, join me to maybe learn a little bit about the history of computing and get a few behind- the-scenes insights into what's happening today. Stick around. [MUSIC] CHRISTINA WARREN: Hello, and welcome to Behind the Tech. I’m Christina Warren, senior cloud advocate at Microsoft. KEVIN SCOTT: And I’m Kevin Scott. CHRISTINA WARREN: Today on the show, our guest is Oren Etzioni. Oren is a professor, entrepreneur, and is the chief executive officer for the Allen Institute for AI. So, Kevin, I’m guessing that you guys have already crossed paths in your professional pursuits. KEVIN SCOTT: Yeah, I’ve been lucky enough to know Oren for the past several years.
    [Show full text]