Harold Abelson - US grants

This is a proposal to build cost-effective specialized computers for scientific computation. A set of hardware and software will be developed to allow rapid construction of very specialized computers: computers that are capable of running exactly one program. The computers are built from many data path parts, interconnected to reflect the control flow of the program to be executed. Several of these computers are under construction for different problems, including the n-body problem of predicting planetary motions, some electronic simulation problems, and large-scale particle simulations. Comparison with other computational approaches to this problem will allow an accurate evaluation of this technique.

9528128 Abelson "Partial Support for the ACM Sixth Conference on Computers, Freedom, and Privacy" This award helps underwrite speaker travel and publication of proceedings for this conference to be held Cambridge MA in March, 1996. The conference is interdisciplinary, and addresses the potential effects on society and individual freedom and privacy resulting from the use of computers, data banks, computer networks, and communications systems. NSF has provided partial support for the last four annual conferences.

The Transparent Accountable datamining Initiative (TAMI) Project is creating technical, legal, and policy foundations for transparency and accountability in large-scale aggregation and inferencing across heterogeneous information systems. The incorporation of transparency and accountability into decentralized systems such as the Web is critical to help society manage the privacy risks arising from the explosive progress in communications, storage, and search technology. The expansion of government use of large-scale data mining for law enforcement and national security provides a compelling motivation for this work. While other investigations of the impact of data mining on privacy focus on limiting access to data as a means of protecting privacy, a variety of social, political, and technical factors are making it increasingly difficult to limit collection of and access to personal information. This Project is addressing the risks to privacy protection and the reliability of conclusions drawn from increasing ease of data aggregation from multiple sources by creating methods and technologies for adding increased transparency and accountability of the inferencing and aggregation process itself. The project is developing precise rule languages that are able to express policy constraints and reasoning engines that are able to describe the results they produce.

Public Policy Advisory Council composed of public policy officials from US Government and other organizations will meet periodically to evaluate the implications of the research and to influence its direction to be relevant to the needs of users.

Research results including publications, technical reports, demos, and software components will be available on the Project website [http://dig.csail.mit.edu/TAMI].

Along with technology development, the Project is investigating public policy implications of the research. The results of the Project are being incorporated into two undergraduate courses at MIT and are being made available on MIT's Open CourseWare System [http://ocw.mit.edu/index.html]. Through the involvement with the World Wide Web Consortium (W3C) [http://www.w3.org/] the team is in a unique position to help disseminate the work developed under this project to the industrial community.

Abstract

IIS - 0740093
Workshop on The Living Heritage of Artificial Intelligence Sussman, Gerald J.
Massachusetts Institute of Technology

This proposal is to convene a workshop and begin an extended dialogue on the emergence of "Artificial Intelligence", it's topical evolution over the past 50 years and begin a process of developing possible roadmaps of future work in AI informed by an analysis of the successes and failures of the past. Simultaneously, it will produce a plan and suggest processes for the preservation of key materials from past research milestones in ways that facilitate new discoveries and new perspectives. From a preservation research perspective, special challenges exist with regard to artifactual materials such as tapes, punch cards, documents, hardware and the interfaces to the materials. One theme of the workshop will address current preservation efforts from a variety of perspectives and backgrounds.

The project on the Theory and Practice of Accountable Systems investigates computational and social properties of information networks necessary to provide reliable assessments of compliance with rules and policies governing the use of information. In prior research, project leaders have demonstrated that achieving basic social policy goals in open information networks will require increased reliance on information accountability through after-the- fact detection of rule violations. This approach stands in contrast to the traditional mechanisms of policy compliance in network environments that rely on security technology to enforce rules by denial of access to resources at risk of abuse. So, access-based systems must be supplemented with accountability-based systems. To ensure that accountable systems can provide a stable, reliable, trustworthy basis on which to ground social policy arrangements in the future, it is necessary: 1) to research practical engineering approaches to designing these systems at scale, and 2) to develop a theory of the operating dynamics of accountable systems in order to establish what types of accountability assessments can be made, when those assertions are reliable, and what vulnerabilities accountable systems may have to attack, intrusion and manipulation. The key hypothesis to be tested regarding Information Accountability is that people are more likely to comply with rules (social or legal) if they believe that their non-compliance will be noticed. Successful study and development of accountable systems will ultimately enable real people, communities and institutions to take advantage of Information Accountability as a means of achieving better privacy and compliance with other information usage rules.

The goals of this project are to develop collaborative tools for helping to solve difficult managerial and societal problems and to test these tools on an important problem confronting the world today: global climate change. Inspired by systems like Wikipedia and Linux, the project will develop a global, on-line forum - called the Climate Collaboratorium - in which thousands of people around the world can create, analyze, and ultimately select detailed plans for what humans can do about global climate change. At the core of the system will be an evolving collection of user-created plans based on computer simulations of the actions humans can take and the predicted impacts of those actions. Users will also be able to debate the pros and cons of different plans and vote for the plans and arguments they find most credible and desirable.

Intellectual merit
The primary intellectual contributions of this work will be lessons about how to design large-scale model-centric collective decision-making tools and the communities to use them.

Broader impacts
At a minimum, this on-line forum can help educate the general public about the real issues involved in global climate change. But more importantly, by constructively engaging a broad range of scientists, policy makers, and ordinary citizens, this forum may help develop plans and policies that are actually better than any that would have otherwise been developed. In short, it could become a combination of a kind of simulation game for climate change, a Wikipedia for controversial topics, and an electronic democracy on steroids.

This project develops the Propagator Model, a concurrent decentralized
framework designed to support computing in large, open, dynamic
environments. It provides powerful tools for organizing computations
to operate effectively in a world of rapidly changing and globally
inconsistent data by adopting a fundamental shift in viewpoint: the
things manipulated by basic computing elements are not fixed values.
Rather, they are information about values, and this information is
continually refined as new information becomes available.

This project creates the architectural and linguistic foundations for
systems that can operate effectively in environments where there is no
central management, and where one cannot rely on resources being
consistently available or consistently operating, and where the data is
rapidly changing and globally inconsistent. Using three mechanisms
implicit in the computational substrate: (1) constraint propagation,
(2) partial information structures, and (3) dependencies, systems
built on the propagator model automatically have the ability to
support their conclusions with arguments and report on the provenance
of the ingredients. They can automatically discover and use
consistent subsystems of inconsistent data.

This project erects a naturally concurrent and distributed model and
infrastructure for computation that makes it easier to build systems
that are reliable in the face of natural failures and deliberate
attacks. It provides support for auditable and accountable systems
that are robust and adaptable to novel applications.

The goal of this project is to develop a system that combines the strengths of both human and computer capabilities to help solve a complex societal problem: global climate change. The project will develop an on-line community called the Climate CoLab, in which many thousands of people around the world create, analyze, and ultimately select detailed plans for what humans can do about climate change. At the core of the system will be an evolving collection of user-created proposals based on computer simulations of the actions humans can take and the predicted impacts of those actions. Users will also be able to debate the pros and cons of different proposals and vote for the proposals and arguments they find most credible and desirable. By integrating three capabilities (computer simulation models, on-line debates, and electronic voting) in a novel way, the system lets a very large group of people define and evaluate alternative problem solutions while computers do the rapid calculations needed to assess key consequences of each alternative. By including relevant experts from different disciplines and members of the public who have novel points of view, the community can consider a wide range of plausible alternatives. And by involving policy makers and large numbers of citizens, the eventual political adoption of the most promising alternatives is facilitated.

Intellectual merit: The primary intellectual contributions of this work will be generalizable lessons about how to design large-scale, on-line communities that use computational models to help solve difficult societal and managerial problems.

Broader impacts: The project will help educate the general public about the issues involved in global climate change. In addition, by constructively engaging a broad range of scientists, policy makers, and concerned citizens, this system may help develop plans and policies that are actually better than any that would have otherwise been developed.

This project introduces undergraduate students to computational thinking (CT) by engaging them to create apps for mobile phones and tablets that are both useful and personally meaningful. CT is a 21st century STEM literacy whose concepts are needed by informed citizens and workers to solve problems and understand complex systems in many domains.

In this project, students learn CT by creating mobile apps using App Inventor, a visual blocks-based programming environment. The project is developing online curricular modules that use mobile app programming to teach CT principles and mobile computing design concepts. These modules include web-based tutorials, video lectures, screencasts, programming exercises, and quizzes --- online materials that give students more in-class time to engage in active learning. Several introductory and intermediate courses are being developed based on these modules. The project is also devising, testing, and evaluating new techniques for assessing students' CT knowledge in the context of mobile computing and project-based courses.

In partnership with MIT's new Center for Mobile Learning, this project is widely disseminating curricular materials, course designs, and assessment rubrics, and is building a national community of undergraduate educators focused on teaching CT via mobile computing.

This project reflects mobile computing's transformation of society by building a curriculum in which undergraduates learn CT not by merely using apps, but by creating them. The materials developed in this project will support both novice and intermediate students in constructionist learning and in design, innovation, and entrepreneurship activities that connect computer science to other disciplines.

The ubiquity of computing technology and the Internet have created an age of big data that has the potential to greatly enhance the efficiency of our societies and the well-being of all people. The trend comes with problems that threaten to prevent or undermine the benefits. An immediate concern is how to fuse, integrate and analyze data while respecting privacy, security and usage concerns. A second issue is allowing data to remain distributed, enabling its owners to maintain and control quality as well as to enforce security and privacy policies. A final underlying challenge is helping to produce sound and useful results by assuring that systems understand the meaning of the data being integrated and analyzing access and usage policies. For some domains, like health informatics and clinical research, solving these problems will have a significant impact on society.

This project explores an approach to solving these problems by developing a policy-compliant integration system for linked healthcare data. The system models data, schemas and policies using open Web standards such as Semantic Web languages, federates queries to independent Linked Data stores based on content, provides policy enforcement by modifying incompliant queries, and uses formal methods to guarantee correctness of key components.

This project provides new approaches to solving one of the most significant problems our society faces in the 21st century: benefiting from the integration of distributed linked data while respecting security, privacy, and usage requirements. The prototype tools and systems are incorporated into our educational activities and made available to others via appropriate open source licenses.

This full scale/collaborative research project targets underserved youth who will collaborate with STEM professionals to co-create community-relevant technology and media content creating a potentially scalable model. App Lab DIY is a collaboration between Youth Radio, the MIT Media Lab's Center for Mobile Learning, and the Mozilla Foundation.

There are multiple and well integrated project strategies. Youth working with professionals will design, create, and disseminate original apps that engage users around community issues (e.g. urban wildlife mapping; Community DNA). They will work directly with the MIT Media Lab/Mobile Learning Center to improve App Inventor, an open-source tool. Youth participants will create media content for national on-air and online outlets including NPR. They will design digital badges to validate and document what they've learned creating media and apps. Curricular resources and tools for educators will be created and disseminated to advance STEM learning among underserved youth.

Deliverables include: 1) creation of three apps (media-rich, STEM-relevant, community valued) that engage communities; 2) improvements in App Inventor, MIT's open-source tool that democratizes app develop for and by all; 3) radio stories that are integrated with the apps; 4) a multimedia toolkit for informal and formal educators to adapt in their programs; 5) a pilot badging system to mark mastery of skills associated with youth-driven media production and technological innovation; and 6) a research study focusing on the use of app development to drive STEM learning and engagement among underserved youth.

Original research will be conducted by an embedded Scholar-in-Residence to inform and advance the field about driving STEM engagement via media/tech innovation. The Scholar-in-Residence will use Participant-Action-Research to inform and improve practice and study the big general questions about how the program works and why.

The evaluation will leverage the instruments and methods established in Youth Radio's past NSF grants to study the impact on the youth's skills, knowledge and attitudes. They will also study impacts on two additional audiences: educators using the multimedia toolkit and users of the mobile apps.

Approximate 1000 Youth Radio students will participate in the project over the three years through contributions to app development, radio production, and digital badges creation. The multimedia toolkit will be nationally disseminated to STEM educators with a large potential reach.

As a part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds research and innovative resources for use in a variety of settings. This media and technology project will scale up Youth Radio's proven model of STEM education through youth-driven multimedia journalism and related app development using the MIT App Inventor. A new Youth News Network (YNN) will implement a nationwide feeder system of youth reporters and educators using the previously developed and proven STEM curriculum. Previous research and evaluation has demonstrated that this model can engage underserved youth and put them in leadership positions in technological innovation. Key deliverables include the YNN STEM Desk that will produce 15-20 STEM-related stories each year; bootcamps (1-3 day workshops) training youth around the country focusing on app development and media links; and new toolkits providing resources to help with app development, data analysis and other STEM-specific skills. Project partners include MIT Media Lab, National Public Radio, Best Buy's Teen Tech Centers, National Writing Project, Computer Clubhouses, and PBS Learning Media among others.

Over the previous eight years, research and evaluation findings had been used to refine the project. These data served as the foundation for this scale-up project. The research conducted by the investigator and the Scholar-in-Residence in this scale-up uses an embedded ethnographic approach that combines field notes, recorded meetings and discussions, media artifacts, etc.--data that is transcribed and coded for indicators of STEM learning and critical computational literacy. The external summative evaluation will build on prior evidence regarding how this unique model engages youth and impacts their skills in STEM related media and technology.

As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative research, approaches and resources for use in a variety of settings.

Despite the ubiquity of Artificial Intelligence (AI), public understanding of how it works and is used is limited This project will research, design, and develop innovative approaches focusing on Artificial Intelligence (AI) for under-represented youth ages 14-24. Program components include live social media chats with AI leaders, app development, journalistic investigations of ethical issues in machine learning, and review of AI-based consumer products. Youth Radio is a non-profit media and tech organizations that provides youth with skills in STEM, journalism, arts, and communications. They engage 250 youth annually through free after-school classes and work shifts. Participants are 90% youth of color and 80% low income. Project partners include the MIT Media Lab which developed App Inventor which allows novice users to build fully functional apps. Staff from Google will serve as a project advisor on the curriculum. The project has exceptional national reach through the dissemination of its media and apps through national outlets such as NPR and Teen Vogue as well as various platforms including online, on-air, as well as presentations, publications, and training tools. The project broadens participation by engaging these low income youth of color in developing skills critical to the workforce of the future. It will help prepare an upcoming generation of Artificial Intelligence creators, users, and consumers who understand the technology and embrace and encourage its potential.It will give them the necessary knowledge and opportunities for careers in an AI-driven future.

This project is grounded in sociocultural learning theory and practice and is interdisciplinary by design. The theoretical framework holds that Computational Thinking plus Critical Pedagogy leads to Critical Computational Literacy. Also, Digital Age Civics plus Participatory Culture leads to Civic Imagination helping youth build a better world through technology. The driving research questions include: What do underrepresented youth understand about AI and its role in society? What are the ethical dilemmas posed by AI from their vantage point? What are the features of an engaging ethics-centered pedagogy with AI? What impact do the AI products developed by the youth have on the target audience? The research design will use ethnographic techniques and design research to study and analyze youth learning. Data sources will include baseline surveys, audio recordings and transcriptions from learning sessions with the participants, research analytic memos, focus group interviews, student-generating artifacts of learning and finished products, etc. The design-based approach will enable systematic, evidence-based iteration on the initiative's activities, pedagogical approach and products. An independent summative evaluation will provide complementary data and perspective to triangulate with the research findings.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.