DOCSLIB.ORG

Public Response to RFI on AI

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Public Response to RFI on AI White House Office of Science and Technology Policy Request for Information on the Future of Artificial Intelligence Public Responses September 1, 2016 Respondent 1 Chris Nicholson, Skymind Inc. This submission will address topics 1, 2, 4 and 10 in the OSTP’s RFI: • the legal and governance implications of AI • the use of AI for public good • the social and economic implications of AI • the role of “market-shaping” approaches Governance, anomaly detection and urban systems The fundamental task in the governance of urban systems is to keep them running; that is, to maintain the fluid movement of people, goods, vehicles and information throughout the system, without which it ceases to function. Breakdowns in the functioning of these systems and their constituent parts are therefore of great interest, whether it be their energy, transport, security or information infrastructures. Those breakdowns may result from deteriorations in the physical plant, sudden and unanticipated overloads, natural disasters or adversarial behavior. In many cases, municipal governments possess historical data about those breakdowns and the events that precede them, in the form of activity and sensor logs, video, and internal or public communications. Where they don’t possess such data already, it can be gathered. Such datasets are a tremendous help when applying learning algorithms to predict breakdowns and system failures. With enough lead time, those predictions make pre- emptive action possible, action that would cost cities much less than recovery efforts in the wake of a disaster. Our choice is between an ounce of prevention or a pound of cure. Even in cases where we don’t have data covering past breakdowns, algorithms exist to identify anomalies in the data we begin gathering now. But we are faced with a challenge. There is too much data in the world. Mountains of data are being generated every second. There is too much data for experts to wade through, and that data reflects complex and evolving patterns in reality. That is, neither the public nor the private sectors have the analysts necessary to process all the data generated by our cities, and we cannot rely on hard-coded rules to automate the analyses and tell us when things are going wrong (send a notification when more than X number of white vans cross Y bridge), because the nature of events often changes faster than new hard-coded rules can be written. One of the great applications of deep artificial neural networks, the algorithms responsible for many recent advances in artificial intelligence, is anomaly detection. Exposed to large datasets, those neural networks are capable of understanding and modeling normal behavior – reconstructing what should happen – and therefore of identifying outliers and anomalies. They do so without hard-coded rules, and the anomalies they detect can occur across multiple dimensions, changing from day to day as the neural nets are exposed to more data. That is, deep neural networks can perform anomaly detection that keeps pace with rapidly changing patterns in the real world. This capacity to detect new anomalies is causing a shift in fraud detection practices in financial services, and cybersecurity in data centers; it is equally relevant to the governance of urban systems. The role of these neural networks is to surface patterns that deserve more attention. That is, they are best used to narrow a search space too large for human analysts, and the flag for them a limited number of unusual patterns that may precede a crisis, failure or breakdown. Artificial intelligence, public health and the public good At the center of medical practice is the act of inference, or reaching a conclusion on the basis of evidence and reasoning. Doctors and nurses learn to map patients’ symptoms, lifestyles and metadata to a diagnosis of their condition. Any mathematical function is simply a way of mapping input variables to an output; that is, inference is also at the heart of AI. The promise of AI in public health is to serve as a automated second opinion for healthcare professionals; it has the ability to check them when they slip. Because an algorithm can be trained on many more instances of data – say, X-rays of cancer patients – than a healthcare professional can be exposed to in a single lifetime, an algorithm may perceive signals, subtle signs of a tumor, that a human would overlook. This is important, because healthcare professionals working long days under stressful conditions are bound to vary in their performance over the course of a given day. Introducing an algorithmic check, which is not subject to fatigue, could keep them from making errors fatal to their patients. In the longer-term, reinforcement learning algorithms (which are goal oriented and learn from rewards they win from an environment) will be used to go beyond diagnoses and act as tactical advisors in more strategic situations where a person must choose one action or another. For now, various deep-learning algorithms are good at classifying, clustering and making predictions about data. Given symptoms, they may predict the name of the underlying disease. Given an individual’s metadata, activity and exercise logs, they may predict the likelihood that that person will face the risk of heart disease. And by making those inferences sooner, more efficiently and more accurately than previous methods, such algorithms put us in a position to alleviate, cure or altogether avoid the disease. To broaden the discussion beyond healthcare, AI is leading us toward a world of (slightly) fewer surprises. It is putting us in a position to navigate the future that we are able to perceive, in germ, in the present. That trend should be kept in mind whenever and wherever we are faced with outcomes that matter (for example, disasters, disease or crime), and data that may correlate to them. Visibility will increase. Indeed, while criminal risk assessment has undergone negative publicity recently (https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal- sentencing), newer algorithms and bigger datasets will make pre-crime units possible. We may see a shift from punitive enforcement to preventative interventions. The legal implications are important, and those in governance should require transparency for all algorithms that filter and interpret data for the judicial system and law enforcement agencies. The social and economic implications of AI As AI advances and its breakthroughs are implemented by large organizations more widely, its impact on society will grow. The scale of that impact may well rival the steam engine or electricity. On the one hand, we will more efficiently and accurately process information in ways that help individuals and society; on the other, the labor market will be affected, skill sets will be made obsolete, and power and wealth will further shift to those best able to collect, interpret and act on massive amounts of data quickly. Deep technological changes will throw people out of work, reshape communities, and alter the way society behaves, connects and communicates collectively. The automation of trucking through driverless vehicles, for example, will affect America’s 3.5 million truckers and the more than 5 million auxiliary positions related to trucking. The same can be said for taxis, delivery and ride-haling services. If history is any indication, our governmental response to disruptions in the labor market will be insufficient. In the hardest-hit sectors, workers, families and communities will suffer and break down. Unemployment, drug use and suicides will go up, along with political instability. Policies such as “basic income” or the Danish “flexicurity” should be explored as ways to soften the blow of job loss and fund transitional retraining periods. The role of “market-shaping” approaches Just as DARPA helped finance the explosion in data science in the Python community through repeated grants to such key players as Continuum, government agencies are in a position to support the researchers, technologies, tools and communities pushing AI in promising directions. • Initiatives focused on Java and the JVM will pave the way for AI to be implemented by large organizations in need of more accurate analytics. This includes government agencies, financial services, telecommunications and transport, among others. • Grants related to embeddable technologies will help AI spread to edge devices such as cell phones, cars and smart appliances. On personal devices such as phones or cars, various forms of inference might allow people to make better decisions about lifestyle, nutrition or even how run their errands. • Initiatives that focus on gathering high-quality datasets and making them public could vastly improve the performance of algorithms trained on that data, much as Li Fei Fei’s work on ImageNet helped usher in a new era of computer vision. Respondent 2 Joyce Hoffman, Writer I am most interested in safety and control issues, and yes, I agree that AI should be developed to the utmost. Respondent 3 kris kitchen, Machine Halo Artificial Intelligence Immune System should be thought about. Billions of friendly AI agents working to identify and act on nefarious agents. Respondent 4 Daniel Bryant, Kaufman Rossin This response is relevant to #8 directly and #6 tangentially. I am a software engineer that primary uses web development tools to build business solutions and have implemented machine learning in relevant algorithms. One of the core items holding back some of the most interesting applications of AI in practice is the lack of available data. Machine learning is the literal embodiment of garbage in, garbage out. The PDF format, while great for it’s time, has significantly impaired the ability of AI to process information. AI must regularly rely on the often poor results of OCR in order to attempt to extract the information that is contained in the PDF.
Load more

Recommended publications
  • A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society1 Barbara J
    A Century Long Commitment to Assessing Artificial Intelligence and Its Impact on Society1 Barbara J. Grosz, Harvard University, Inaugural Chair of the AI100 Standing Committee Peter Stone, University of Texas at Austin, Chair of the Inaugural AI100 Study Panel The Stanford One Hundred Year Study on Artificial Intelligence, a project that launched in December 2014, is designed to be a century-long periodic assessment of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society. Colloquially referred to as "AI100", the project issued its first report in September 2016. A Standing Committee works with the Stanford Faculty Director of AI100 in overseeing the project and designing its activities. A little more than two years after the first report appeared, we reflect on the decisions made in shaping it, the process that produced it, its major conclusions, and reactions subsequent to its release. The inaugural AI100 report [4], which is titled “Artificial Intelligence and Life in 2030,” examines eight domains of human activity in which AI technologies are already starting to affect urban life. In scope, it encompasses domains with emerging products enabled by AI methods and ones raising concerns about technological impact generated by potential AI-enabled systems. The Study Panel members who authored the report and the AI100 Standing Committee, which is the body that directs the AI100 project, intend for it to act as a catalyst, spurring conversations on how we as a society might shape and share the potentially powerful technologies that AI could enable. In addition to influencing researchers and guiding decisions in industry and governments, the report aims to provide the general public with a scientifically and technologically accurate portrayal of the current state of AI and its potential.
    [Show full text]
  • The Book of Apigee Edge Antipatterns V2.0
    The Book of Apigee Edge Antipatterns Avoid common pitfalls, maximize the power of your APIs Version 2.0 Google Cloud ​Privileged and confidential. ​apigee 1 Contents Introduction to Antipatterns 3 What is this book about? 4 Why did we write it? 5 Antipattern Context 5 Target Audience 5 Authors 6 Acknowledgements 6 Edge Antipatterns 1. Policy Antipatterns 8 1.1. Use waitForComplete() in JavaScript code 8 1.2. Set Long Expiration time for OAuth Access and Refresh Token 13 1.3. Use Greedy Quantifiers in RegularExpressionProtection policy​ 16 1.4. Cache Error Responses 19 1.5. Store data greater than 512kb size in Cache ​24 1.6. Log data to third party servers using JavaScript policy 27 1.7. Invoke the MessageLogging policy multiple times in an API proxy​ 29 1.8. Configure a Non Distributed Quota 36 1.9. Re-use a Quota policy 38 1.10. Use the RaiseFault policy under inappropriate conditions​ 44 1.11. Access multi-value HTTP Headers incorrectly in an API proxy​ 49 1.12. Use Service Callout policy to invoke a backend service in a No Target API proxy 54 Google Cloud ​Privileged and confidential. ​apigee 2 2. Performance Antipatterns 58 2.1. Leave unused NodeJS API Proxies deployed 58 3. Generic Antipatterns 60 3.1. Invoke Management API calls from an API proxy 60 3.2. Invoke a Proxy within Proxy using custom code or as a Target 65 3.3. Manage Edge Resources without using Source Control Management 69 3.4. Define multiple virtual hosts with same host alias and port number​ 73 3.5.
    [Show full text]
  • Alphabet's 2019 CDP Climate Change Report
    Alphabet, Inc. - Climate Change 2019 C0. Introduction C0.1 (C0.1) Give a general description and introduction to your organization. As our founders Larry and Sergey wrote in the original founders' letter, "Google is not a conventional company. We do not intend to become one." That unconventional spirit has been a driving force throughout our history -- inspiring us to do things like rethink the mobile device ecosystem with Android and map the world with Google Maps. As part of that, our founders also explained that you could expect us to make "smaller bets in areas that might seem very speculative or even strange when compared to our current businesses." From the start, the company has always strived to do more, and to do important and meaningful things with the resources we have. Alphabet is a collection of businesses -- the largest of which is Google. It also includes businesses that are generally pretty far afield of our main internet products in areas such as self-driving cars, life sciences, internet access and TV services. We report all non- Google businesses collectively as Other Bets. Our Alphabet structure is about helping each of our businesses prosper through strong leaders and independence. We have always been a company committed to building products that have the potential to improve the lives of millions of people. Our product innovations have made our services widely used, and our brand one of the most recognized in the world. Google's core products and platforms such as Android, Chrome, Gmail, Google Drive, Google Maps, Google Play, Search, and YouTube each have over one billion monthly active users.
    [Show full text]
  • Technology, Development and Economic Crisis: the Schumpeterian Legacy
    CIMR Research Working Paper Series Working Paper No. 23 Technology, development and economic crisis: the Schumpeterian legacy by Rinaldo Evangelista University of Camerino Piazza Cavour, 19/F, 62032 Camerino (IT) +39-0737-403074 [email protected] June 2015 ISSN 2052-062X Abstract This contribution aims at highlighting the complex, non-linear and potentially contradictory nature of the relationships between technological progress, economic growth and social development, in particular within the context of market based economies. The main (provocative) argument put forward in the paper is that the recent neo-Schumpeterian literature, while providing fundamental contributions to our understanding of innovation, has contributed to the rising of a positivistic reading of the relationship between technology, economy and society, with technology being able to guaranty strong economic growth and (implicitly) social welfare. This is confirmed by the fact that, contrary to other influential heterodox economic schools and Schumpeter himself, in the recent neo- Schumpeterian literature technology is only rarely associated to macroeconomic market failures such as systemic crises, structural unemployment, and the growth of social and economic inequalities. It is also argued that the emergence of a “positivistic bias” in the neo-Schumpeterian literature has been associated to the dominance of a supply-side and micro-based view of the technology-economy relationships. Key words: Technology, Innovation, Schumpeter, Development, Crisis JEL codes: B52, O00, O30. 2 1. Introduction There is no doubt that the last economic crisis, with its depth, extension and length, could have, at least in principle, the potentiality of shaking at the fundamentals the dominant neo-liberal economic thinking and policy framework.
    [Show full text]
  • Technology Policy and the Environment
    SUSTAINABLE DEVELOPMENT « Technology Policy and the Environment What is the role of technology and technology policy in addressing environmental concerns and realising sustainable development goals? To consider this question, a Workshop on Technology Policy Technology Policy and the Environment was held in Paris on 21 June 2001 as part of the OECD Horizontal Programme on Sustainable Development. This brochure contains a summary of the workshop discussions, which and the Environment focused on the contributions of economic theory and modelling to understanding technology/ environment relationships. Participants debated the role and design of technology policy in addressing environmental problems and developed a list of recommendations for future OECD work. The insights gained at the workshop will contribute to further OECD analysis on technology and sustainable development. SUSTAINABLE DEVELOPMENT www.oecd.org 2000 Technology Policy and the Environment ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT Pursuant to Article 1 of the Convention signed in Paris on 14th December 1960, and which came into force on 30th September 1961, the Organisation for Economic Co-operation and Development (OECD) shall promote policies designed: – to achieve the highest sustainable economic growth and employment and a rising standard of living in Member countries, while maintaining financial stability, and thus to contribute to the development of the world economy; – to contribute to sound economic expansion in Member as well as non-member countries in the process of economic development; and – to contribute to the expansion of world trade on a multilateral, non-discriminatory basis in accordance with international obligations. The original Member countries of the OECD are Austria, Belgium, Canada, Denmark, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States.
    [Show full text]
  • Artificial Intelligence, Big Data and Cloud Computing 144
    Digital Business and Electronic Digital Business Models StrategyCommerceProcess Instruments Strategy, Business Models and Technology Lecture Material Lecture Material Prof. Dr. Bernd W. Wirtz Chair for Information & Communication Management German University of Administrative Sciences Speyer Freiherr-vom-Stein-Straße 2 DE - 67346 Speyer- Email: [email protected] Prof. Dr. Bernd W. Wirtz Chair for Information & Communication Management German University of Administrative Sciences Speyer Freiherr-vom-Stein-Straße 2 DE - 67346 Speyer- Email: [email protected] © Bernd W. Wirtz | Digital Business and Electronic Commerce | May 2021 – Page 1 Table of Contents I Page Part I - Introduction 4 Chapter 1: Foundations of Digital Business 5 Chapter 2: Mobile Business 29 Chapter 3: Social Media Business 46 Chapter 4: Digital Government 68 Part II – Technology, Digital Markets and Digital Business Models 96 Chapter 5: Digital Business Technology and Regulation 97 Chapter 6: Internet of Things 127 Chapter 7: Artificial Intelligence, Big Data and Cloud Computing 144 Chapter 8: Digital Platforms, Sharing Economy and Crowd Strategies 170 Chapter 9: Digital Ecosystem, Disintermediation and Disruption 184 Chapter 10: Digital B2C Business Models 197 © Bernd W. Wirtz | Digital Business and Electronic Commerce | May 2021 – Page 2 Table of Contents II Page Chapter 11: Digital B2B Business Models 224 Part III – Digital Strategy, Digital Organization and E-commerce 239 Chapter 12: Digital Business Strategy 241 Chapter 13: Digital Transformation and Digital Organization 277 Chapter 14: Digital Marketing and Electronic Commerce 296 Chapter 15: Digital Procurement 342 Chapter 16: Digital Business Implementation 368 Part IV – Digital Case Studies 376 Chapter 17: Google/Alphabet Case Study 377 Chapter 18: Selected Digital Case Studies 392 Chapter 19: The Digital Future: A Brief Outlook 405 © Bernd W.
    [Show full text]
  • Japanese Technology Policy: History and a New Perspective
    DPRIETI Discussion Paper Series 01-E-001 Japanese Technology Policy: History and a New Perspective HARAYAMA Yuko RIETI The Research Institute of Economy, Trade and Industry http://www.rieti.go.jp/en/ RIETI Discussion Paper Series 01-E-001 JAPANESE TECHNOLOGY POLICY: HISTORY AND A NEW PERSPECTIVE Yuko Harayama Research Institute of Economy, Trade and Industry August 2001 Abstract The last decade of the 20th century was marked by the emergence of a "knowledge-based economy," with governments in most OECD countries intensifying their commitment to the underlying research and development activities. Japan is no exception. The Japanese government affirmed setting the objectives of a "Nation Based on Science and Technology" as the fundamental policy goal in 1980 and since then it has implemented several laws and policy packages in the fields of science, technology, industry and higher education, with the common denominator being "Industry-University- State cooperation." This policy orientation has been consolidated by the Science and Technology Basic Law, introduced in 1995, which gave the government legal competence in science and technology. This trend tends to reinforce stereotypic images of the Japanese innovation system, such as the "government picking up technological paths" or "industry and government working hand-in-hand." Does this perception reflect reality? This study attempts to clarify this by examining: · How the technology policy evolved during the postwar period in Japan; · What its impact was on the private sector's decision on R&D activities; · What the underlying philosophy was of the government's R&D policies, if one existed; · What the new perspective is.
    [Show full text]
  • Google for Education National Parks VR Google Expeditions Google Arts & Culture Be Internet Awesome Made with Code CS First Google Science Fair
    Google For Education National Parks VR Google Expeditions Google Arts & Culture Be Internet Awesome Made with Code CS First Google Science Fair Learn how tools built for teaching and learning, Discover the hidden worlds of our Take a field trip to virtually anywhere (even Explore works of art and stories from around Teach learners the fundamentals of digital Make the connection between coding and Learn the basics of Computer Science using the Create projects that show how Science, like Classroom, G Suite for Education, and National Parks on ranger-guided trips places school buses can’t go) using immersive the world with 360° tours of exhibits in over 70 safety and citizenship so they can be safe, creativity, empowering girls to engage with block-based programming language, Scratch. Technology, Engineering, and Math can be used Chromebooks, can increase engagement through virtual reality. AR and VR technology. different countries. confident explorers of the online world. technology and bring their ideas to life. to impact the world around us. and inspire curiosity. Google for National Google Google Arts Education Parks VR Expeditions & Culture Discover the hidden worlds of Explore works of art and stories Tools built for teaching and learning. Field trips to virtually anywhere. our National Parks. from around the world. Over 80 million teachers and students around the world Take a ranger-guided journey through the glaciers of What if you could journey to the surface of Mars or From The Metropolitan Museum of Art to Nairobi’s communicate and collaborate using Classroom and Alaska’s Kenai Fjords or get up close with active climb to the top of Machu Picchu without ever leaving Kenya National Archives, Google Arts & Culture offers G Suite for Education, while Chromebooks are the most volcanoes in Hawai’i.
    [Show full text]
  • Code Girl Tracey Acosta Santa Clara University
    Santa Clara University Scholar Commons Computer Engineering Senior Theses Engineering Senior Theses 6-1-2015 Code girl Tracey Acosta Santa Clara University Amanda Holl Santa Clara University Paige Rogalski Santa Clara University Follow this and additional works at: https://scholarcommons.scu.edu/cseng_senior Part of the Computer Engineering Commons Recommended Citation Acosta, Tracey; Holl, Amanda; and Rogalski, Paige, "Code girl" (2015). Computer Engineering Senior Theses. 43. https://scholarcommons.scu.edu/cseng_senior/43 This Thesis is brought to you for free and open access by the Engineering Senior Theses at Scholar Commons. It has been accepted for inclusion in Computer Engineering Senior Theses by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Code Girl by Tracey Acosta Amanda Holl Paige Rogalski Submitted in partial fulfillment of the requirements for the degrees of Bachelor of Science Computer Science and Engineering Bachelor of Science in Web Design and Engineering School of Engineering Santa Clara University Santa Clara, California June 1, 2015 Code Girl Tracey Acosta Amanda Holl Paige Rogalski Computer Science and Engineering Web Design and Engineering Santa Clara University June 1, 2015 ABSTRACT Despite the growing importance of technology and computing, fewer than 1% of women in college today choose to major in computer science.[1] Educational programs and games created to interest girls in computing, such as Girls Who Code and Made With Code, have been successful in engaging girls with interactive and creative learning environments, but they are too advanced for young girls to benefit from. To address the lack of educational, computer science games designed specifically for young girls, we developed a web-based application called Code Girl for girls age five to eight to customize their own avatar using Blockly, an open-source visual coding editor developed by Google.
    [Show full text]
  • “Reflections on the Status and Future of Artificial Intelligence”
    STATEMENT OF: ERIC HORVITZ TECHNICAL FELLOW AND DIRECTOR MICROSOFT RESEARCH—REDMOND LAB MICROSOFT CORPORATION BEFORE THE COMMITTEE ON COMMERCE SUBCOMMITTEE ON SPACE, SCIENCE, AND COMPETITIVENESS UNITED STATES SENATE HEARING ON THE DAWN OF ARTIFICIAL INTELLIGENCE NOVEMBER 30, 2016 “Reflections on the Status and Future of Artificial Intelligence” NOVEMBER 30, 2016 1 Chairman Cruz, Ranking Member Peters, and Members of the Subcommittee, my name is Eric Horvitz, and I am a Technical Fellow and Director of Microsoft’s Research Lab in Redmond, Washington. While I am also serving as Co-Chair of a new organization, the Partnership on Artificial Intelligence, I am speaking today in my role at Microsoft. We appreciate being asked to testify about AI and are committed to working collaboratively with you and other policymakers so that the potential of AI to benefit our country, and to people and society more broadly can be fully realized. With my testimony, I will first offer a historical perspective of AI, a definition of AI and discuss the inflection point the discipline is currently facing. Second, I will highlight key opportunities using examples in the healthcare and transportation industries. Third, I will identify the important research direction many are taking with AI. Next, I will attempt to identify some of the challenges related to AI and offer my thoughts on how best to address them. Finally, I will offer several recommendations. What is Artificial Intelligence? Artificial intelligence (AI) refers to a set of computer science disciplines aimed at the scientific understanding of the mechanisms underlying thought and intelligent behavior and the embodiment of these principles in machines that can deliver value to people and society.
    [Show full text]
  • Letters to the Editor
    Articles Letters to the Editor Research Priorities for is a product of human intelligence; we puter scientists, innovators, entrepre - cannot predict what we might achieve neurs, statisti cians, journalists, engi - Robust and Beneficial when this intelligence is magnified by neers, authors, professors, teachers, stu - Artificial Intelligence: the tools AI may provide, but the eradi - dents, CEOs, economists, developers, An Open Letter cation of disease and poverty are not philosophers, artists, futurists, physi - unfathomable. Because of the great cists, filmmakers, health-care profes - rtificial intelligence (AI) research potential of AI, it is important to sionals, research analysts, and members Ahas explored a variety of problems research how to reap its benefits while of many other fields. The earliest signa - and approaches since its inception, but avoiding potential pitfalls. tories follow, reproduced in order and as for the last 20 years or so has been The progress in AI research makes it they signed. For the complete list, see focused on the problems surrounding timely to focus research not only on tinyurl.com/ailetter. - ed. the construction of intelligent agents making AI more capable, but also on Stuart Russell, Berkeley, Professor of Com - — systems that perceive and act in maximizing the societal benefit of AI. puter Science, director of the Center for some environment. In this context, Such considerations motivated the “intelligence” is related to statistical Intelligent Systems, and coauthor of the AAAI 2008–09 Presidential Panel on standard textbook Artificial Intelligence: a and economic notions of rationality — Long-Term AI Futures and other proj - Modern Approach colloquially, the ability to make good ects on AI impacts, and constitute a sig - Tom Dietterich, Oregon State, President of decisions, plans, or inferences.
    [Show full text]
  • What Is X? What Makes a Moonshot? Rapid Evaluation Project
    What is X? Hi, I’m Ben Google [X] was formed to apply Google’s resources to I get excited by tech, making ‘the world’s most intractable problems’. A diverse team of a positive impact on Earth, inventors and entrepreneurs were assembled, working on and anything that pushes the secretive pipe-dream projects, known as moonshots. boundaries of what’s possible. I plan to die on Mars, hopefully not on impact! How might self-driving cars How might kites generate change the way we travel? power in new places? This summer, I moved to Mountain View, California for 6 months to intern at X. ... My skillset Now just called X (of parent company Alphabet), the moonshot factory is known for its ‘graduated’ projects, I work at the intersection of hardware and including Waymo [1], Makani [2], Loon [3] and Wing [4]. How might balloons internet How might drones change software, of design and development. I was connect remote areas? how we deliver goods? hired as a generalist; invaluable in uncertain early-stage prototyping. What makes a moonshot? UI: Developed our first touchscreen interface Moonshots should have social purpose, and be profitable in order to be Code: Built backend in Huge attractive to investors. Generally, every moonshot at X follows this recipe: object-oriented Python problem Huge Problem: Choose a massive problem that, if solved, would positively Firmware: Wrote board-level impact the lives of millions, even billions. I2C protocol drivers Radical Solution: Create and propose a radical new solution to the problem, Break- PCBs: Co-designed new Radical no matter how ridiculous it sounds.
    [Show full text]