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On 19 February 2020, the European Commission published a white paper on the use of artificial intelligence ("AI") in the EU (the "White Paper"). The White Paper forms part of the Commission President, Ursula Von der Leyen's, digital strategy, one of the key pillars of her administration's five year tenure, recognising that the EU has fallen behind the US and China with respect to the strategic deployment of AI. To tackle this problem, the Commission proposes a common EU approach to'speed up the uptake' of AI in the EU, whilst also tackling the human and ethical implications of AI's fast growing use in the EU, including the possible downsides of its use, such as opaque decision making and hidden, embedded gender and racial discrimination. In order to achieve a common EU approach to AI, and to create "trustworthy" AI that can rival developments in the US and China, the Commission proposes the creation of a regulatory framework for AI. Under the regulatory framework, AI applications deemed'high-risk' will be distinguished from'non high-risk' AI applications.

Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he's faced at NASA, including building an implementation of Google's Show & Tell algorithm for image captioning using TensorFlow. He was involved in the Mars rover landing mission, where he was working in a planetary data system engineering node, helping to build a data management framework called object-oriented data technology to support capturing, processing and sharing of data for NASA's scientific archives. He contributes to open source as a former Director at the Apache Software Foundation, and teaches graduate courses at USC in Content Detection and Analysis, and in Search Engines and Information Retrieval. In this episode, Chris opens the show discussing his interest in data.

Over the last century, scientists have developed methods to map the structures within the Earth's crust, in order to identify resources such as oil reserves, geothermal sources, and, more recently, reservoirs where excess carbon dioxide could potentially be sequestered. They do so by tracking seismic waves that are produced naturally by earthquakes or artificially via explosives or underwater air guns. The way these waves bounce and scatter through the Earth can give scientists an idea of the type of structures that lie beneath the surface. There is a narrow range of seismic waves -- those that occur at low frequencies of around 1 hertz -- that could give scientists the clearest picture of underground structures spanning wide distances. But these waves are often drowned out by Earth's noisy seismic hum, and are therefore difficult to pick up with current detectors.

These are unprecedented times, at least by information age standards. Much of the U.S. economy has ground to a halt, and social norms about our data and our privacy have been thrown out the window throughout much of the world. Moreover, things seem likely to keep changing until a vaccine or effective treatment for COVID-19 becomes available. All this change could wreak havoc on artificial intelligence (AI) systems. Garbage in, garbage out still holds in 2020. The most common types of AI systems are still only as good as their training data.

Jose-Marie Griffiths is a commissioner on the National Security Commission on Artificial ... [ ] Intelligence. Jose-Marie Griffiths was born and raised in London where she earned a Bachelor's degree in Physics, a PhD in Information Science and a Post Doctorate in Computer Science and Statistics. She has taught at University of California, Berkeley, done research for various US government agencies and is now president of South Dakota's Dakota State University. She was named a commissioner on the National Security Commission on Artificial Intelligence in 2019. At the commission, Dr. Griffiths heads a line of effort focused on raising understanding of AI in the federal government and streamlining the government's hiring practices to make it easier to bring young AI practitioners into national security roles.

If anything, the importance and potential of Artificial Intelligence in the KYC space is underplayed and underrated. The industry has been under immense pressure in the past couple of years with regulations and scandals redefining the means and ways you go about Know Your Customer procedures. In the midst of this disarray, AI has emerged as the guiding light, the savior the compliance space was calling for. What does AI mean for compliance, what's the role of this new3 technology and what problems does it really solve? The idea that Artificial Intelligence will replace humans is ignorant, to say the least.

Some biases in AI might be necessary to satisfy critical business requirements, but how do we know if an AI recommendation is biased strictly for business necessities and not other reasons? A company receives 1000 applications for a new position, but whom should it hire? How likely is a criminal to become a repeat offender if they are released from prison early? As artificial intelligence (AI) increasingly enters our lives, it can help answer those questions. But how can we manage the biases that are in the data sets that AI uses? "AI decisions are tailored to the data that is available around us, and there have always been biases in data, with regards to race, gender, nationality, and other protected attributes.

Terrorists from across the borders entering India are often exploiting weaknesses in border infrastructure and use technology and cyberspace to create technology to propagate their thinking.crimes. And are continuously supported from beyond the Indian borders, primarily misusing modern technology for funding or Command and Control purposes. Prevention of violent extremism in India is an important and necessary requirement for the country. Such efforts need multi-dimensional coordination between Armed Forces and various National law enforcement agencies. Today's asymmetric warfare requires newer tools and techniques to keep pace with the changing times.

As the future of work rapidly evolves, and organizations are integrating people, technology, alternative workforces, and new ways of working, leaders are wrestling with an increasing range of resulting ethical challenges. These challenges are especially pronounced at the intersection between humans and technology, where new questions have risen to the top of the ethics agenda about the impact of emerging technologies on workers and society. How organizations combine people and machines, govern new human-machine work combinations, and operationalize the working relationship between humans, teams, and machines will be at the center of how ethical concerns can be managed for the broadest range of benefits. Organizations that tackle these issues head-on--changing their perspective to consider not only "could we" but also "how should we"--will be well positioned to make the bold choices that help to build trust among all stakeholders. The Readiness Gap: Seventy-five percent of organizations say ethics related to the future of work are important or very important for their success over the next 12 to 18 months, but only 14 percent say they are very ready to address this trend.