On Thursday, September 20, 2018, the Michael Dukakis Institute (MDI), together with AI World, successfullyorganized the first AIWS Conference based on the theme: AI-Government and AI Arms Races and Norms.
Distinguished Professor Governor Michael Dukakis – Chairman of MDI moderated this conference.
Opening Remark by Governor Michael Dukakis – Chairman of the Michael Dukakis Institute for Leadership and Innovation (MDI) at the AIWS Conference
Key highlights of the conference include:
– Introducing the concepts of AI-Government, and the AIWS Index.
– Prof. Matthias Scheutz, Director of the Human-Robot Interaction Laboratory at Tufts University presented ideas of controlling technology for AI systems and robots, ensuring safety and ethical standards.
– Prof. Joseph Nye, Harvard University addressed the problem of norms for AI.
– Prof. Marc Rotenberg, President of Electronic Privacy Information Center (EPIC) presented the transparency of algorithm.
– Introduced the strategic collaboration between MDI and AI World – The industry’s largest conference and expo on the business and technology of AI for enterprise.
– Introduced the idea for an AIWS Square.
The concepts of AI-Government were presented for the first time during the AIWS conference. In addition, the AIWS Index for AI Ethics of Governments is also being studied by MDI and strategic partners. According to Prof. Nazli Choucri, AI-Government is the mechanism by which government operates and AI brings out the diversity in the decision-making process. Three points by Prof. Choucri on how to make AI-Government work are: provision of human oversight, improvement of responsiveness through feedbacks demands and pressures on government and potential corrective mechanisms by government, prevention of the excessive centralized control of any entity used in the AI for governments.
Prof. Nazli Choucri, Member of BGF’s Board of Thinkers, Cyber-politics Director of MDI, Professor of Political Science at MIT at the AIWS Conference
Prof. Matthias Scheutz, Director of the Human-Robot Interaction Laboratory at Tufts University presented his ideas of controlling technology for AI systems and robots to ensure safety and ethical standards for humanity. “AI and robotics technology will both ultimately require built-in ethical constraints to ensure that the technology is safe and beneficial to humans” said Prof. Scheutz. The greatest danger is when algorithms are out of control and people can’t decide what the systems can and will learn in the future. He also pointed out as false some common prevention solutions which he believes are basically insufficient to safeguard AI and robotic technologies. Therefore, Prof. Scheutz believes it is essential to design AI systems from the ground up, even from the hardware level, with ethical provisions that include social and moral norms, ethical principles, and laws that the system cannot ignore and must use in its initial operation.
Prof. Matthias Scheutz, Member of MDI’s AIWS Standards and Practice Committee, Director of the Human-Robot Interaction Laboratory of Tufts University at the AIWS Conference
“Many of the debates around the employment of AI techniques have the same focus with the debates associated with the use of computing technology and government agencies back in the 1960s and 1970s”, said Prof. Marc Rotenberg, President of Electronic Privacy Information Center (EPIC). In Prof. Rotenberg’s opinion, the core interest and the protection of privacy is not about secrecy or confidentiality, it is about the fairness of the processing concerning data on individuals. Part of the problem is that as these systems have become more sophisticated, they have also become more opaque. These systems are widespread and have enormous impact on the lives of individuals, for that reason, individuals have the right to know the movement of automated decisions. Together with EPIC, Prof. Rotenberg is sending the message to the United States Congress that algorithmic transparency will be key in the AI age to foster public participation and policy formulation.
Prof. Marc Rotenberg, Member of MDI’s AIWS Standards and Practice Committee, President of EPIC at the AIWS Conference
Prof. Joseph Nye opened his speech by talking about the expansion of Chinese firms in the US market and their ambition to surpass the US in the field of AI. Prof. Nye believes the idea of an AI arms race and geopolitical competition in AI that can have profound effects on our society, however, he says prediction that China will be ahead of the US on AI by 2030 is “uncertain” and “indeterminate” since China’s only advantage is having more data and little concern about privacy. Talking about the norms for AI, Prof. Nye thinks that as people unleashes AI, which is leading to warfare and autonomy of offensives, we should have a treaty to control it. One of his suggestion is that we have international institutions which will essentially monitor the various programs in AI in various countries.
Prof. Joseph Nye, Member of BGF’s Board of Thinkers, Distinguished Service Professor of Harvard University at the AIWS Conference
Notably in this conference, MDI officially introduced the cooperation with AI World – The industry’s largest conference and expo on the business and technology of enterprise AI. This cooperation marks the determination between two organizations, toward the aim of developing, measuring, and tracking the progress of ethical AI policy-making and solution adoption among governments and corporations. On this event, Eliot Weinman – Chairman of AI World Conference and Expo also became a member of AIWS Standards and Practice Committee.
The AIWS Conference at Harvard Faculty Club, September 20, 2018
In this conference, the MDI launches the initiatives of building AI Time Square, a place for originating and developing ideals and noble human values in the AI Age. AI Square would include AIWS House to introduce achievements of the 7 AI Application layers in a society in which AI is comprehensively applied to all aspects of the society and life. This initiative is hoped to create a symbol of human culture in the era of AI, especially for the 21th century.
At the AIWS Conference, Professor Matthias Scheutz – Director of the Human-Robot Interaction Laboratory at Tufts University gave a keynote speech about the potential of AI and robotics technologies and called for ethical provisions for the design of AI systems from the outset to prevent accidental failures.
Prof. Matthias Scheutz, Member of MDI’s AIWS Standards and Practice Committee, Director of the Human-Robot Interaction Laboratory of Tufts University at the AIWS Conference
In his speech, Prof. Scheutz showed that the greatest risk caused by AI and robotics technologies is when unconstrained machine learning is out of control where AI systems acquire knowledge and start to pursue goals that were not intended by their human designer. For example, if an AI program operating in the power grid decides to cut off energy in certain areas for better power utilization overall, it will however leave millions of people living without electricity, which consequently turns out to be an AI accidental failure. He also points out as false some common preventive solutions inside and outside the system which he believes are basically insufficient to safeguard AI and robotics technologies. Even with “emergency buttons”, the system itself might finally set its own goal to prevent the shutdown set up previously by human.
According to Professor Matthias Scheutz, the best way to safeguard AI systems is to really build-in ethical provisions directly into the learning algorithms, the reasoning algorithms, the recognition algorithms, etc. so that the algorithm itself has such provisions. The simple form of “ethical testing” to catch and handle ethical violations was also demonstrated in his presentation.
Scheutz is a Professor in Cognitive and Computer Science in the Department of Computer Science, Director of the Human-Robot Interaction Laboratory and the new Human-Robot Interaction Ph.D. program, and Bernard M. Gordon Senior Faculty Fellow in the School of Engineering at Tufts University. He has more than 300 peer-reviewed publications in artificial intelligence, natural language processing, cognitive modeling, robotics, and human-robot interaction. His current research focuses on complex interactive autonomous systems with natural language and machine learning capabilities. He is a member of AIWS Standards and Practice Committee.
In the AIWS Conference on September 20, 2018, scholars and leaders from governments, businesses and universities gathered, discussed and exchanged ideas around the theme of AI Government.
Mr. Nguyen Anh Tuan, CEO of BGF, Director of MDI at the AIWS Conference
The concept of AI-Government was developed at the Michael Dukakis Institute for Leadership and Innovation through the collaboration of Governor Michael Dukakis, Mr. Nguyen Anh Tuan, Professor Nazli Choucri, and Professor Thomas Patterson and first presented in the AIWS Conference in 2018.
In the future, AI is believed to be able to transform the public sector by automating tasks. However, it cannot replace governance by humans or human decision-making processes but guides and informs them. Therefore, it needs ethical standards to prevent harmful intentions. Additionally, the AIWS Index about AI Ethics of Governments is also being studied by MDI and strategic partners.
Speaking of the challenges lying ahead, Prof. Marc Rotenberg, President of Electronic Privacy Information Center (EPIC), Member of AIWS Standards and Practice Committee brought up the rapidly increasing gap between informed government decision-making and the reality of our technology-driven world, which he warns, “governments may ultimately lose control of these systems” if they don’t take action.
Prof. Marc Rotenberg, President of EPIC on AI-Government
A recent breakthrough in computer vision has given robot the ability to differentiate objects.
MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has recently made progress in computer vision that lets machines identify objects and take actions without knowledge about the object.
The system “Dense Object Nets” (DON) developed by CSAIL now can create “visual roadmaps” of the object’s points, the robot will teach itself to understand and manipulate the items, enabling it to pick it up. This has been a breakthrough in this area of work, as a variety of advances couldn’t inspect the specific parts of an object according to Ph.D. student Lucas Manuelli. It is viewed as a potential use not only for manufacturing, but also for household application due to its self-supervised feature for some specific tasks such as putting plates onto a shelf while you are on vacation. In the future, the team hopes to make more improvements so that it can understand objects deeply like cleaning a desk.
Another issue should not be ignored is its ability to execute action without supervision. According to Layer 1 of the AIWS 7-Layer Model, machines and technology should be created with concern over human’s prosperity and safety. It should be carefully supervised, and programmed to avoid malfunction and further damage.
Researchers at chip company Nvidia, the Mayo Clinic, and the MGH & BWH Center for Clinical Data Science have built an algorithm which can creates various data sets for medical AI to study.
For artificial intelligence to work effectively, it relies on its set of information. A study accomplished under the collaboration of Nvidia, the Mayo Clinic, and MGH & BWH Center for Clinical Data Science has created a system that can produce diverse set of medical data. It created synthetic scans depicting abnormalities from existing MRIs of brain tumors using generative adversarial networks (GANs).
The system is a cutting-edge tool for training neural networks, but medical data will require more complication as “the data are usually imbalanced” said Hoo Chang Shin, a research scientist at Nvidia.
There is a great deal of abnormalities in medical cases that might be difficult for AI to diagnose as most of the data was programmed here. AI should be trained carefully before facing real-life situation especially in healthcare.
