The History of AI (HAI) at AIWS.net, Michael Dukakis Institute is the first historical site in AI

Mission: Governor Michael Dukakis said on March 10, 2020 at UCLA: “study history to avoid mistakes from the past, learn great lessons from history for today and tomorrow”. The mission of HAI is to do so, in addition to shaping a better future and...

The History of AI (HAI) at AIWS.net, Michael Dukakis Institute is the first historical site in AI

  Boston, 04/15/2020 Mission: Governor Michael Dukakis said on March 10, 2020 at UCLA: “study history to avoid mistakes from the past, learn great lessons from history for today and tomorrow”. The mission of HAI is to do so, in addition to...

Announcement

The History of AI” will be announced on May 5, 2020, at the Online AIWS Roundtable the Transatlantic Approaches on Digital Governance: A New Social Contract in Artificial Intelligence (AI) Age, which is organized by Boston Global Forum and World Leadership...

Discussion from the AIWS Roundtable: Transparency is not a luxury

The world’s current growing pandemic of the Wuhan virus amplifies the paramount and ultimate goal of our AI initiative.  Our vision is to establish a universal AI value system ensuring that AI technology advancement would make lives better and not...

A solution to reopen in democratic countries

Boston, April 18, 2020 The economic devastation caused by the coronavirus has been swift. Tens of millions of jobs lost; retail sales have collapsed; and industrial production has fallen precipitously. But even as the government remains focused on containing...

Graphical Models for Processing Missing Data

This paper reviews recent advances in missing data research using graphical models to represent multivariate dependencies. We first examine the limitations of traditional frameworks from three different perspectives: \textit{transparency, estimability...

Full Law Identification In Graphical Models Of Missing Data: Completeness Results

Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser Missing data has the potential to affect analyses conducted in all fields of scientific study, including healthcare, economics, and the social sciences. Several approaches to unbiased inference in the presence...

CAUSAL RELATIONAL LEARNING

Babak Salimi, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, Dan Suciu Causal inference is at the heart of empirical research in natural and social sciences and is critical for scientific discovery and informed decision making. The gold standard...

Causal Inference in Machine Learning

Ricardo Silva Department of Statistical Science and Centre for Computational Statistics and Machine Learning [email protected]   Researchers reviewed 47 nutrition studies and concluded that children and adolescents who ate breakfast had better...