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Anthony J. Ferrante, Global Head of Cybersecurity and Senior Managing Director, FTI Consulting, Inc.

Artificial intelligence (AI) models are built with a type of machine learning called deep neural networks (DNNs), which are similar to neurons in the human brain. DNNs make the machine capable of mimicking human behaviors like decision making, reasoning and problem solving. This presentation will discuss the security, ethical and privacy concerns surrounding this technology. Learning Objectives:1: Understand that the solution to adversarial AI will come from a combination of technology and policy.2: Learn that coordinated efforts among key stakeholders will help to build a more secure future.3: Learn how to share intelligence information in the cybersecurity community to build strong defenses.

//I personally think Putin is causing a massive (record breaking) humanitarian crisis on purpose with the bombings he has done in populated cities so far. Here is why (thread):\.


“I personally think Putin is causing a massive (record breaking) humanitarian crisis on purpose with the bombings he has done in populated cities so far. Here is why (thread):”

Public policy includes efforts by governmental as well as nongovernmental agencies (other than professional associations) to manage genetic enhancement. For example, the International Olympic Committee has a policy on performance-enhancing drugs in sport. In the United States, the Food and Drug Administration classified synthetic anabolic steroids as a restricted class of drugs, making it more difficult to get access to them. Such measures will not always be successful. Epoetin alfa (EPO) is a useful medication for the many people who suffer from chronic anemia, including people who must undergo regular renal dialysis. As a consequence, it is in very wide supply for legitimate therapeutic purposes, unlike the synthetic anabolic steroids. Imposing strict limitations on access to EPO would create an enormous inconvenience for the large number of people who benefit from the drug. The fact that some athletes are able to get their hands on EPO is an unintended consequence of having the drug widely available for legitimate therapeutic uses. The appropriate public policy will not be the same, necessarily, for every drug.

By “personal policy” we mean the moral understandings and social practices of individuals, parents, and families, including those moral convictions that would cause them to refrain from unwise or unfair use of genetic enhancement technologies. The Worth of a Child, for example, focuses on ethical issues involving children and parents.11 How does one engage that sort of personal policy response? The means we have are limited but powerful: education, public dialogue, and the encouragement of ethical reflection.

In conclusion, there are four points worth reiterating. First, as we think about genetic enhancement, we should use a broad definition of genetic-enhancement technologies, not merely gene manipulation, but indirect genetic technologies, such as biosynthetic drugs. Second, we should try to anticipate the enhancement temptations of new therapies. Such anticipation may help us in shaping the marketing, availability, or other aspects of those technologies. Third, we should promote the adoption of appropriate public and professional policies. Finally, we should provide public education and dialogue to encourage personal ethical reflection on the appropriate uses and limits of genetic-enhancement technologies.

The Future Of Space Tech & Innovation — Dr. Joel Mozer Ph.D., Director of Science, Technology & Research, United States Space Force.


Dr. Joel Mozer is the Director of Science, Technology, and Research, United States Space Force (https://www.spaceforce.mil/).

With a PhD in Physics, and MS in Atmospheric Science, from University of Arizona, Dr. Mozer serves as the principal scientific advisor to the Commander and is the senior authority for all science and technology matters for an organization of approximately 11,000 space professionals worldwide, and manages a global network of satellite command and control, communications, missile warning and launch facilities. In this role, he interacts with other principals, operational commanders, combatant commands, acquisition, and international communities to address cross-organizational science and technical issues and solutions.

Elon Musk has always said that Neuralink, the company he created in 2016 to build brain-computer interfaces, would do amazing things: Eventually, he says, it aims to allow humans to interact seamlessly with advanced artificial intelligence through thought alone. Along the way, it would help to cure people with spinal cord injuries and brain disorders ranging from Parkinson’s to schizophrenia.

Now the company is approaching a key test: a human clinical trial of its brain-computer interface (BCI). In December, Musk told a conference audience that “we hope to have this in our first humans” in 2022. In January, the company posted a job listing for a clinical trial director, an indication that it may be on track to meet Musk’s suggested timeline.

Musk has put the startup under unrelenting pressure to meet unrealistic timelines, these former employees say. “There was this top-down dissatisfaction with the pace of progress even though we were moving at unprecedented speeds,” says one former member of Neuralink’s technical staff, who worked at the company in 2019. “Still Elon was not satisfied.” Multiple staffers say company policy, dictated by Musk, forbade employees from faulting outside suppliers or vendors for a delay; the person who managed that relationship had to take responsibility for missed deadlines, even those outside their control.

Accelerating Research To Prevent & Cure Disease — Dr. Kevin Perrott, Ph.D., Founder & CEO, OpenCures; Co-Founder & Treasurer, SENS Research Foundation


Dr. Kevin Perrott, Ph.D. is Founder and CEO, OpenCures (https://opencures.org/), Adjunct Professor, University of Alberta, Co-Founder and Advisor, Oisin Biotechnologies, President, of Global Healthspan Policy Institute, and Co-Founder and Treasurer, SENS Research Foundation.

Kevin is a successful entrepreneur and owner of the largest motorcycle and snowmobile dealership in Canada, Riverside Honda and Skidoo Sales in Edmonton, Alberta. He became a cancer survivor, an experience which clearly highlighted the deficiencies of the current health technology development paradigm where the customer has almost no input in the development of their own health solutions. Armed with the realization that nothing is more valuable than health and the time to enjoy it with those you love, Kevin resolved to put his energies towards addressing these deficiencies.

Second, we need to be aware of the manifest biases and fallacies that magnify the weight humans put on potential losses compared to potential future gains. As a result of these biases, humans often seek to preserve the status quo over pursuing activities that lead to future changes, even when the expected (but risky) gains from the latter may outweigh those of maintaining the status quo. The preference for the status quo, and neat narratives that oversimplify complex scenarios, can lead to overlooking (or ignoring) important information that is not consistent with the current generally accepted meme — illustrated, perhaps, in Musk’s continued optimism for autonomous vehicles despite the evidence leading to others downscaling their forecasts.

The first and second points together lead to the third important consideration: the importance of independently verified data over forecasts and opinion in determining the need for and appropriateness of policy interventions. And data is historical by nature. Pausing to collect it rather than rushing to respond is recommended.

To that end, we can use available data to analyze whether increasing use of AI is demonstrably affecting key labor market performance indicators: labor productivity and multifactor productivity growth. If, as Keynes suggests, AI-driven technological change is increasing the potential for new means of economizing the use of labor to outrun the pace of finding new ways to use it, we would expect to see both statistics rising in the era dominated by AI. Yet as Figures 1 and 2 show, the exact opposite appears true for a wide range of OECD countries. Neither does the data suggest that other key labor market indicators have changed negatively with the advent of AI. As with the computer industry, we see the effects of AI everywhere but in the productivity statistics.

What is AI, really? Jeff Dean, the head of Google’s AI efforts, explains the underlying technology that enables artificial intelligence to do all sorts of things, from understanding language to diagnosing disease — and presents a roadmap for building better, more responsible systems that have a deeper understanding of the world. (Followed by a Q&A with head of TED Chris Anderson)

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