Black-box explanation is the problem of explaining how a machine learning model -- whose internal logic is hidden to the auditor and generally complex -- produces its outcomes. Current approaches for solving this problem include model explanation, outcome explanation as well as model inspection. While these techniques can be beneficial by providing interpretability, they can be used in a negative manner to perform fairwashing, which we define as promoting the perception that a machine learning model respects some ethical values while it might not be the case. In particular, we demonstrate that it is possible to systematically rationalize decisions taken by an unfair black-box model using the model explanation as well as the outcome explanation approaches with a given fairness metric. Our solution, LaundryML, is based on a regularized rule list enumeration algorithm whose objective is to search for fair rule lists approximating an unfair black-box model. We empirically evaluate our rationalization technique on black-box models trained on real-world datasets and show that one can obtain rule lists with high fidelity to the black-box model while being considerably less unfair at the same time.

Why the American Civil Liberties Union is calling out Amazon's facial recognition tool, and what the ACLU found when it compared photos of members of Congress to public arrest photos. Facial-detection technology that Amazon is marketing to law enforcement often misidentifies women, particularly those with darker skin, according to researchers from MIT and the University of Toronto. Privacy and civil rights advocates have called on Amazon to stop marketing its Rekognition service because of worries about discrimination against minorities. Some Amazon investors have also asked the company to stop out of fear that it makes Amazon vulnerable to lawsuits. The researchers said that in their tests, Amazon's technology labeled darker-skinned women as men 31 percent of the time.

A special message from MSN: The UK's most vulnerable children and young people face unimaginable challenges. We've partnered with giving platform Benevity to raise funds for two charities - the NSPCC and The Children's Society – to try to help turn things around for them. You can help make a difference - please donate now. Open up the photo app on your phone and search "dog," and all the pictures you have of dogs will come up. This was no easy feat. Your phone knows what a dog "looks" like.

The release of Tesla's Autopilot Hardware 3.0 is just around the corner and the automotive firm has made a number of significant changes with this upgrade. A series of recent patents have confirmed that Tesla will utilize a new artificial intelligence chip, or "neural net accelerator". This will replace the NVIDIA hardware that is currently used in the Autopilot 2.0 platform and should enable full self-driving capabilities in the future. Why is Tesla working on a new AI chip? According to the patent filed with the United States Patent and Trademark Office, "Processing for machine learning and artificial intelligence typically requires performing mathematical operations on large sets of data and often involves solving multiple convolution layers and pooling layers."

Chinese telecom giant Huawei is at the centre of an increasingly tense standoff between China and the US. What began as a trade spat and grievances over corporate intellectual property theft has developed into a global standoff involving "hostage diplomacy", death sentences and allegations of Chinese espionage. Huawei's senior executive Meng Wanzhou, was arrested in Canada in December over allegations of sanctions violations, and awaits extradition to the US. Meanwhile, three Canadians remain in police custody in China – with one of them sentenced to death this month. Washington, meanwhile, has said it will file a formal extradition request for Meng by the 30 January deadline.

The price paid by the transferees does not correspond to the software itself, which in itself has little value, but to the secret scientific procedures that the software has implemented in it. These procedures are registered under the formula of industrial secret. The technology to be transferred incorporates an artificial intelligence system that involves a specialized advisory service that adapts case by case to the needs of the client. According to the modalities actually analyzed, in this case a contract has been signed by which the license to use temporarily or permanently a software containing procedures that allow theoretically determine various situations for marketing. In accordance with the case law of the Supreme Court (inter alia, STS of 30 May 2002; of 19 December 2002 or of 2 October 1999), it is essential to distinguish contracts for the assignment or licensing of know-how from contracts for technical assistance, both of which are distinct from contracts for the transfer of technology.

Published by the Royal Society.

While much of the mainstream discussion around AI focuses on the two biggest technology players, the USA and China, other initiatives from around the world are quietly leading the way. In many ways the UK has also positioned itself as a leader in this space through the creation of the Centre for Data Ethics and Innovation and the Regulators Pioneer Fund. Canada is taking strong action on responsible AI use in government and will be the first country to implement a directive laying out the rules of applying algorithms in the public sphere. Similarly, while the US still lacks any federal laws on self-driving cars, countries like Austria and Singapore are pursuing comprehensive approaches to modernising the entirety of their transportation systems towards autonomous mobility. Such initiatives include a straightforward regulatory environment, large-scale public-private partnerships and they address a range of issues around autonomous mobility that go beyond technology-readiness levels, from infrastructural requirements to societal acceptance.

In a healthy display of tech innovation power, Chinese companies have been dominating blockchain and artificial intelligence (AI) patents in 2017. According to a new study by UHY, an accounting and consultancy network, 99 patents (32%) from a total of 314 filed with the World Intellectual Property Organisation (WIPO) in 2017 were by Chinese firms. Rick David, chairman of UHY, comments: "Blockchain and AI could unlock significant economic growth over the coming decades, and businesses across the world are investing in making sure they benefit from that." He adds: "Where countries are lagging behind in areas such as these, governments should consider tax incentives to encourage increased research and development." While that Chinese figure is impressive – and note that all this data is from 2017, US businesses were close behind with 29% of blockchain patents, followed by Australian businesses with 40 patents (13%).

This week at the World Economic Forum (WEF), an annual gathering that put tech executives at the same table as far-right Brazilian president Jair Bolsonaro, Salesforce CEO Marc Benioff called San Francisco the canary in the coal mine. "San Francisco is kind of a train wreck; we have a real inequality problem," he said. Benioff and Salesforce, which has the largest skyscraper on the San Francisco skyline, led the Prop C campaign, a $300 million business tax aimed at reducing homelessness in San Francisco that is currently held up in court. Benioff also asserted at the gathering in Davos, Switzerland that artificial intelligence is "a new human right" that all people deserve. "Those who have the artificial intelligence will be smarter, will be healthier, will be richer, and of course, you've seen their warfare will be significantly more advanced," he said.