As we edge closer to the end of a very eventful year, it seemed like a good time for a follow up to "12 Amazing Women in AI Ethics to Follow in 2018" post, which left out many deserving voices who are furthering the cause of Ethical and Responsible Artificial Intelligence (AI). We live in very challenging times. The pervasiveness of bias in AI algorithms and autonomous "killer" robots looming on the horizon, all of which necessitate an open discussion and immediate action to address the perils of unchecked AI. The decisions we make today will determine the fate of future generations. Ethics in AI or Responsible AI is a broad evolving discipline that covers wide spectrum of critical issues facing humanity today, including how we can eliminate racial/gender inequities perpetuated by algorithmic biases to whether robots should have rights.

It has become commonplace to assert that autonomous agents will have to be built to follow human rules of behavior-social norms and laws. But human laws and norms are complex and culturally varied systems; in many cases agents will have to learn the rules. This requires autonomous agents to have models of how human rule systems work so that they can make reliable predictions about rules. In this paper we contribute to the building of such models by analyzing an overlooked distinction between important rules and what we call silly rules --rules with no discernible direct impact on welfare. We show that silly rules render a normative system both more robust and more adaptable in response to shocks to perceived stability. They make normativity more legible for humans, and can increase legibility for AI systems as well. For AI systems to integrate into human normative systems, we suggest, it may be important for them to have models that include representations of silly rules.

China now has seminars to teach other countries how to censor free speech as its'techno-dystopia' spreads, a worrying report has found. Governments worldwide are stepping up use of online tools to suppress dissent and tighten their grip on power, a human rights watchdog study found. Chinese officials have held sessions on controlling information with 36 of the 65 countries assessed, and provided telecom and surveillance equipment to a number of foreign governments, researchers said. India led the world in the number of internet shutdowns, with over 100 reported incidents in 2018 so far, claiming that the moves were needed to halt the flow of disinformation and incitement to violence. Many governments, including Saudi Arabia, are employing'troll armies' to manipulate social media and in many cases drown out the voices of dissidents.

The report shows that digital technologies are likely to further reduce trade costs and boost trade significantly, especially in services and for developing countries. Global trade is projected to grow by an additional 2 percentage points annually between 2016 and 2030 as a result of digitalization, falling trade costs and the increased use of services. The share of services in global trade is projected to grow from 21 per cent in 2016 to 25 per cent in 2030. The report also finds that the reduction in trade costs could be especially beneficial for micro, small and medium sized enterprises (MSMEs) and firms from developing countries, provided they have the ability to keep up with the adoption of digital technologies. In the best scenario, developing and least-developed economies' share in global trade is predicted to grow to 57 per cent by 2030, from 46 per cent in 2015, whereas if they cannot keep up, this share is predicted to rise to 51 per cent.

The US Justice Department indicted two companies based in China and Taiwan and three individuals saying they conspired to steal trade secrets from US semiconductor company Micron relating to its research and development of memory storage devices. The charges against Taiwan-based United Microelectronics Corp, China state-owned Fujian Jinhua Integrated Circuit, Co, Ltd, and three individuals mark the fourth case brought since September as part of a broader crackdown against alleged Chinese espionage on US companies. US Attorney-General Jeff Sessions told a news conference that Chinese espionage has been "increasing rapidly", adding "cheating must stop". He said the government is launching a new initiative to crack down on Chinese espionage trade cases. In addition to the criminal case, the Justice Department also filed a civil lawsuit seeking to prevent the two companies from exporting any products created using trade secrets.

Thousands of Google employees and contractors around the globe--many of them women--briefly walked off the job Thursday to protest Google's handling of sexual harassment claims and other workplace issues, and to demand more transparency around harassment incidents and pay levels at the company. The demonstrations took place outside about 40 Google offices, including Singapore, London, New York, San Francisco, and the company's headquarters in Mountain View, California. The protest was spurred by a recent New York Times article about Google awarding multimillion-dollar exit packages to top male executives accused of sexual misconduct, including a $90 million payment to Android founder Andy Rubin, even after Google investigators found credible a claim that Rubin coerced a female employee into performing oral sex. In San Francisco, workers carried signs saying "Not OK Google" and "Equal Pay 4 Equal Work." Organizers led the crowd in chants like "Time's up for Google," and read accounts of workplace harassment from anonymous Google employees, who did not share their names.

A machine learning model may exhibit discrimination when used to make decisions involving people. One potential cause for such outcomes is that the model uses a statistical proxy for a protected demographic attribute. In this paper we formulate a definition of proxy use for the setting of linear regression and present algorithms for detecting proxies. Our definition follows recent work on proxies in classification models, and characterizes a model's constituent behavior that: 1) correlates closely with a protected random variable, and 2) is causally influential in the overall behavior of the model. We show that proxies in linear regression models can be efficiently identified by solving a second-order cone program, and further extend this result to account for situations where the use of a certain input variable is justified as a "business necessity". Finally, we present empirical results on two law enforcement datasets that exhibit varying degrees of racial disparity in prediction outcomes, demonstrating that proxies shed useful light on the causes of discriminatory behavior in models.

You would hope intelligent human beings would be able to agree on core moral standpoints for technologies, and for some this certainly seems achievable. Discussing the ethics of AI, though, is far more complex than simply agreeing not to fly your drone into a person. To work within the real world, AI has to be aware of the nuances and particulars of specific societies. An AI system in a high surveillance country might differ from its equivalents in other parts of the world. Then, of course, there is ethical divide within societies.

The modernization of the computer system was a key part of reforms promised by Gov. John Hickenlooper in 2012 after The Denver Post and 9News reviewed the cases of 72 children whose families or caregivers were known to the state's child protection system before their deaths. The investigation found a lack of coordination between county and state officials, funding inequities and overburdened workers.

Public Knowledge, a Washington, DC advocacy group, today released a paper calling for the formation of a new federal government authority to develop expertise and capacity on artificial intelligence (AI), to be able to effectively regulate and govern these technologies in the future. The paper, The Inevitability of AI Law & Policy: Preparing Government for the Era of Autonomous Machines, was released on 31 October and written by Ryan Clough, general counsel at Public Knowledge. The paper "argues that the rapid and pervasive rise of artificial intelligence risks exploiting the most marginalized and vulnerable in our society." In order to mitigate these harms, a new national authority on AI will be needed, it says, to "provide the rest of the government with the expertise and experience needed to achieve five goals crucial to building ethical AI systems: