Data Science Insider: January 29th, 2021

In this week’s Super Data Science newsletter: Becoming a Chief Data Scientist. MIT Creates ‘Liquid’ Machine Learning. US Has 'Moral Imperative' to Develop AI Weapons. Amazon and USC Partner to Create ML Research Center. The Biden Administration and AI. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [Becoming a Chief Data Scientist]( brief: This article in Silicon Republic takes an interview with Anodot’s co-founder and chief data scientist, Ira Cohen, and uses it to examine the role of a chief data scientist. The article is part of a series, which serves to explain the variety of different roles that one may have whilst working in data. Cohen current position at the US analytics company sees him responsible for helping businesses to detect anomalies in revenue alongside customer interactions and he has previously served as chief data scientist at Hewlett-Packard Enterprise. He sees the role as the one which bridges the gap between management and data science teams. He argues that the role is the one responsible for bringing ML innovation from ideas supported by big data to fruition as working implementations. Cohen states: “Truly great chief data scientists know how to walk a fine line between driving creative innovation and pragmatic solutions.” Why this is important: Here at SuperDataScience we aim to offer you the tools to achieve your career aims. By understanding what different roles are available in data science, you can both understand your industry better and potentially work towards becoming a chief data scientist yourself! [Click here to find out!]( [MIT Creates ‘Liquid’ Machine Learning]( brief: Researchers at MIT say they have developed a flexible algorithm that can change its underlying equations to continuously adapt to new inputs of data. It's hoped this new approach could revolutionise technology that relies on decision-making protocols where the data changes over time, or in unpredictable environments, such as medical diagnosis or autonomous driving. Most neural networks have fixed behaviour and they typically don't adjust all that well to changes in incoming data streams. However, this neural network has the potential to avoid these issues by using a set of differential equations as the base of its algorithm, potentially creating a more fluid type of ML. The idea is inspired by the microscopic nematode, Caenorhabditis (C) elegans, which has only 302 neurons in its nervous system. Ramin Hasani, the study's lead author, and his team used equations that allowed the parameters of his neural network to change over time. Why this is important: According to Hasani, time-series data are both ubiquitous and vital to our understanding of the world. Most neural networks’ behaviour is fixed after the training phase, which means they’re bad at adjusting to changes in the incoming data stream. Hasani says the fluidity of his “liquid” network makes it more resilient to unexpected or noisy data. [Click here to read on!]( [US Has 'Moral Imperative' to Develop AI Weapons]( In brief: The US should continue to explore the development and use of AI-powered autonomous weapons despite calls for them to be banned, a commission led by former Google boss Eric Schmidt has concluded. The government-appointed panel filed a draft report to Congress on Tuesday after two days of discussions centered on the use of artificial intelligence by the world’s biggest military power. Robert Work, the panel’s vice chairman and a former deputy secretary of defence, said autonomous weapons are expected to make fewer mistakes than humans do in battle, leading to reduced casualties or skirmishes caused by target misidentification. "It is a moral imperative to at least pursue this hypothesis," he said. For about eight years, a coalition of non-governmental organizations has pushed for a treaty banning "killer robots," saying human control is necessary to judge attacks' proportionality and assign blame for war crimes. Why this is important: While autonomous weapon capabilities are decades old, concern has mounted with the development of AI to power such systems, along with research finding biases in AI and examples of the software's abuse. The US panel, called the National Security Commission on Artificial Intelligence, in meetings this week acknowledged the risks of autonomous weapons. A member from Microsoft Corp for instance warned of pressure to build machines that react quickly, which could escalate conflicts. [Click here to discover more!]( [Amazon and USC Partner to Create ML Research Center]( In brief: Amazon is helping to create a ML and AI research lab at the University of Southern California. The Center for Secure and Trusted Machine Learning, part of USC’s Viterbi School of Engineering, will support research that looks at new scalable ways to secure and preserve privacy in ML. Amazon and USC are establishing the center together and it will be directed by Salman Avestimehr, professor of computer and electrical engineering at USC, who will also oversee related fellowships and the overall project. The expectation is that the center will unleash a new line of fundamental research on privacy and security aspects of ML. Each year, the center will provide support for research projects focused on the development of new methodologies for secure and privacy-preserving ML solutions that can scale to support billions of users. In addition, the center will provide annual fellowships to doctoral students working in this research area. Why this is important: The creation of a research center looking at privacy and security is timely and critical, given the proliferation of AI across all aspects of society from education to finance, transportation, healthcare, and many others. However, the involvement of Amazon is likely to raise some eyebrows, due controversy over their own privacy record when it comes to AI implemented products, such as Alexa. [Click here to see the full picture!]( [The Biden Administration and AI]( In brief: At the moment, the most pressing issues on the new US President’s table are fighting the coronavirus pandemic, providing financial relief for Americans, and reversing a series of Trump-era policies. AI, as expected, hasn’t yet made it to the top of list. But Joe Biden has given several signals already about how his administration might think about and treat the technology, which are explored in this article by Verdict. One of the key areas for analysis is the fact that Biden elevated the director of the Office of Science and Technology Policy (OSTP) to a cabinet-level position, and appointed top geneticist Eric Lander, the founding director of the MIT-Harvard Broad Institute, to the role as well as also appointing sociologist Alondra Nelson as OSTP deputy director. The OSTP advises the president on science and technology issues and guides science and technology policy and budget making across the government. Why this is important: Here at SuperDataScience we’ve frequently covered the policies and decisions regarding AI of the Trump administration, which was often criticized for seeing AI chiefly as a geopolitical tool. It’s too early, as yet, to know how things will differ under Biden but the early signs suggest that there will be a shift in focus towards scientific advancement. Of course, we will continue to cover developments as they happen. [Click here to find out more!]( [SuperDataScience podcast]( In this week's [SuperDataScience Podcast](, Deblina Bhattacharjee joins us to discuss her amazing past experience and current work in computer vision and how data scientists can excel in the field. --------------------------------------------------------------- What is the Data Science Insider? This email is a briefing of the week's most disruptive, interesting, and useful resources curated by the SuperDataScience team for Data Scientists who want to take their careers to the next level. Want more conversations like this? Last year, we held our first-ever DSGO Virtual Conferences, where more than 3,500 data scientists gathered to learn, grow, and connect! If you missed them or want to repeat this fantastic experience, stay tuned to our upcoming virtual and in-person events that will take your DS career to the next level. DSGO is your go-to place to elevate your technical skills, gain life-long career lessons from industry experts, and build lasting connections with data-driven peers. If you want to learn more and register for our future events, [click here](. Know someone who would benefit from getting The Data Science Insider? 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