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RECENT VIDEOS

13 Results | Page 1 | Last | Next
 

04.12.2018
36 mins
ILP Video

Superminds: The Surprising Power of People and Computers Thinking Together

Thomas Malone
Patrick J McGovern (1959) Professor of Management
Founding Director, Center for Collective Intelligence (CCI)
MIT Sloan School of Management
If you're like most people, you probably believe that humans are the most intelligent animals on our planet. But there's another kind of entity that can be far smarter: groups of people. In this talk, Thomas Malone, the founding director of the MIT Center for Collective Intelligence, shows how groups of people working together in superminds -- like hierarchies, markets, democracies, and communities -- have been responsible for almost all human achievements in business, government, science, and beyond. And these collectively intelligent human groups are about to get much smarter.

Using dozens of striking examples and case studies, Malone shows how computers can help create more intelligent superminds simply by connecting humans to one another in a variety of rich, new ways. And although it will probably happen more gradually than many people expect, artificially intelligent computers will amplify the power of these superminds by doing increasingly complex kinds of thinking. Together, these changes will have far-reaching implications for everything from the way we buy groceries and plan business strategies to how we respond to climate change, and even for democracy itself. By understanding how these collectively intelligent groups work, we can learn how to harness their genius to achieve our human goals.

Drawing on cutting-edge science and insights from a remarkable range of disciplines, Superminds articulates a bold -- and utterly fascinating -- picture of the future that will change the ways you work and live, both with other people and with computers.
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04.12.2018
20 mins
ILP Video

The Civic Supermind

Matthew Claudel
Designer, Researcher, Writer
DesignX, MIT
The city has always been a product of collective intelligence, a supermind in itself. Today, the innovation economy has profoundly transformed politics, economics, and society, yet its effects have only just begun to manifest in the physical space of cities. Although innovation holds the promise of addressing many challenges of a globalized, urbanized, and climate-changed planet, the present trends in city-technology and city-making demonstrate how the innovation economy can also threaten regulation and policy, exacerbate economic inequality, and fray the social fabric of place.

Matthew Claudel explores these opportunities and frictions. Atomization, distributed networks, and real-time platform markets have opened new territory for urban technology and city-making – what could be thought of as The Civic Supermind. The innovative capacity of atomized but coordinated problem-solving for cities will be more powerful, by orders of magnitude, than individuals working alone. This is an approach to urban technology, already emerging, that harmonizes local specificity with global innovation capacity and economies of scale. It encompasses place-based modes of social organization; innovation in policy, regulation, and codes; and the creation of new place-based capital structures. It connects technology to people in place.
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04.12.2018
36 mins
ILP Video

People, Robots, and the Work of the Future

David Mindell
Frances and David Dibner Professor of the History of Engineering and Manufacturing
Professor of Aeronautics and Astronautics and Engineering Systems
Founder & CEO, Humatics
MIT Program in Science, Technology, and Society
As autonomous systems move out of the research laboratory into operational environments, they need ever deeper connections to their surroundings. Traditional notions of full autonomy — vehicles or robots working entirely on their own, have led to “clockwork” approaches where robots must be isolated from their human surroundings. Instead, we need precise, robust relationships with people and infrastructure. This situated autonomy appears in driverless cars' dependence on human-built infrastructure, the need for new systems of unmanned traffic management in the air, and the increasing importance of collaborative robotics in factories. How can we best design such systems to inhabit and enhance the human world?

In this talk David Mindell sketches a number of these emerging scenarios, traces new technologies to address the problems they raise, and envisions new approaches to human and robotic interaction that helps people and robots work together safely and collaboratively.
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04.12.2018
18 mins
ILP Video

Go See: Looking for Future Talent in Your Current Workforce

Sharon Goh
Senior Manager, Global Software Stability and Integration
Amazon Robotics
Five years ago, Sharon Goh started a journey of collecting stories of drive, determination and grit. Starting with the 15 person customer support team she managed, she asked questions about how they got there, how the company found them, or how they found the company. What she found were stories of loss, pain, fear, joy, and success. These were amazing stories that needed to be told and that deeply impacted her as an executive and opened her eyes to the future of work and the power that managers have right now to influence it. In this short talk, she will share a preview of these stories. She will share common themes and some of the ah-ha moments that she had during this process. Can you drive change starting from the ground up? How do you listen and how do you prepare today for what is coming tomorrow? Her hope is these stories will inspire you and help you rethink the future of work.
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04.12.2018
21 mins
ILP Video

Civic Faith and Meaningful Inefficiencies

Stephen Walter
Program Director, Mayor's Office of New Urban Mechanics
City of Boston
Trusting a data set or an analysis always requires a leap of faith. Beyond an acceptance of margins of error and biases, all data-driven decisions necessitate what William James once called a ?will to believe.? When it comes to data that impact or justify institutional decisions, there first needs to be a will to believe not only in the institution's ability to be honest and rigorous with data, but in the very authority of data itself to tell us something meaningful about the world. In an era of ?alternative facts? and fear-based advocacy, this is a sad truth that we must contend with; but it may also sometimes be a symptom of data tunnel vision - of forgetting to attend to certain aspects of stakeholder engagement that involve the sometimes irrational, sometimes inefficient, but always human need for something more than facts to act from. How can we be better at designing the conditions for people to develop faith in our (and their) ability to do good things with data? And how can purposefully-deployed inefficiencies improve the resilience of human systems?
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04.11.2018
33 mins
ILP Video

Data Science and Artificial Intelligence at IDSS

Munther Dahleh
Director, IDSS
William A. Coolidge Professor, Electrical Engineering and Computer Science
MIT Institute for Data, Systems, and Society
The MIT Intelligence Quest - MIT IQ - will advance the science and engineering of both human and machine intelligence. It seeks to discover the foundations of human intelligence and drive the development of technological tools that can positively influence virtually every aspect of society.

The Institute’s culture of collaboration will encourage life scientists, computer scientists, social scientists, and engineers to join forces to investigate the societal implications of their work as they pursue hard problems lying beyond the current horizon of intelligence research. By uniting diverse fields and capitalizing on what they can teach each other, we seek to answer the deepest questions about intelligence.
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04.11.2018
26 mins
ILP Video

The Challenge of Medical Artificial Intelligence

Leo Celi
MIT Institute for Medical Engineering and Science
Co-Director, MIT Sana
Staff Physician, Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center
Assistant Professor, Harvard Medical School
Medicine presents a particular problem for creating artificial intelligence (AI) because the issues and tasks involved are often neither clearly defined nor black and white. In harsher terms, it is particularly difficult to create ?artificial? intelligence when there are still disagreements about concept definitions, what processes are important, and at times, even what outcomes are desirable. Medicine is a surprisingly subjective endeavor whereas valid and useful AI requires not only reliable, unbiased, and extensive data, but also objective (and similarly, unbiased) definitions and objectives. It makes sense that the early successes in AI applications in healthcare are in the field of image recognition. But image recognition in medicine is a low-hanging fruit. Where we need assistance is in the day-to-day complex decision-making that requires data synthesis and integration, tasks we now approach with what is referred to as clinical intuition. This process is notoriously riddled with cognitive biases and typically based on large information gaps, but is nonetheless generally accepted as representing the ?art? of medicine. Resolving the subjectivity of medicine with the objectivity required for digitization?and the secondary creation of AI?first involves resolution of a number of questions: What do we want to do? What do we need to do? What can we do?
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04.11.2018
33 mins
ILP Video

Build AI products faster, cheaper

Kalyan Veeramachaneni
Principal Research Scientist
MIT Laboratory for Information and Decision Systems
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04.11.2018
26 mins
ILP Video

MIT Cheetah Robot: A New Design Paradigm for Physical Interaction

Sangbae Kim
Associate Professor of Mechanical Engineering
MIT Department of Mechanical Engineering
Read More

04.11.2018
29 mins
ILP Video

MIT Startup Exchange: Introduction and Lightning Talks

Catalant Technologies, Patrick Petitti
Catalia Health, Cory D. Kidd
Cogito, Ali Azarbayejani
IQ3Connect., Ali Merchant
Near Field Magnetics, David McManus
serviceMob, Anuj Bhalla
TVision Insights, Dan Schiffman
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.
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04.11.2018
32 mins
ILP Video

Future will be Measured in nanometers

Vladimir Bulovic
Associate Dean for Innovation, School of Engineering
Fariborz Maseeh Professor of Emerging Technology
MacVicar Faculty Fellow
MIT Department of Electrical Engineering and Computer Science
The Nano Age is upon us … With nano-scale advancements we are reimagining Health and Life Sciences, Energy, Computing, Information Technology, Manufacturing, Quantum Science, … That is because nano is not a specific technology. It does not belong to a particular industry or discipline. It is, rather, a revolutionary way of understanding and working with matter, and it is the key to launching the next Innovation Age, the Nano Age.
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04.11.2018

ILP Video

Redefining Small Business Lending through ML and Social Physics

Gustavo Vinacua
Founder, BBVA Innovation Centers
CEO, Trust-u
Manuel Ventero filled in for Gustavo
Read More

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