Data Science Insider: June 11th, 2021

In this week’s Super Data Science newsletter: US Senate Approves $50bn Boost for Computer Chip and AI Tech. Microsoft’s Kate Crawford on AI. The Latest Trends Data Scientists Should Be Aware Of. Europe’s AI Laws Draw Criticism from Digital Rights Groups. Lessons To Be Learned from Major Internet Outage. 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. --------------------------------------------------------------- [US Senate's $50bn Boost for Computer Chip and AI Tech]( brief: The US Senate has overwhelmingly approved a bill to boost American semiconductor production and the development of AI and other technology. The news stems from growing international competition, most notably from China. The centerpiece of the bill is a $50 billion emergency allotment to the US commerce department to boost semiconductor development and manufacturing through research and incentive programs. Overall, the bill would increase spending by about $250 billion, with most of the spending occurring in the first five years. Joe Biden said he was “encouraged” by the Senate’s passage of the United States Innovation and Competition Act. “We are in a competition to win the 21st century, and the starting gun has gone off,” Biden said. “As other countries continue to invest in their own research and development, we cannot risk falling behind. America must maintain its position as the most innovative and productive nation on Earth.” Why this is important: The 68-32 vote for the bill demonstrates how confronting China economically is an issue that unites both parties in Congress. As we’ve covered extensively here at SuperDataScience, the war between the US and China has become heated over the past few months and this is the latest sign that America will continue to fight for top place. [Click here to find out!]( [Microsoft’s Kate Crawford on AI]( brief: Co-founder of the AI Now Institute at New York University and a researcher at Microsoft and the école Normale Supérieure in Paris - Kate Crawford - is an expert in the political and social implications of AI. In her new book, Atlas of AI, she also looks at the global infrastructure that underpins the rise of this technology. She argues that AI, far from being something abstract and objective, is both material and intrinsically linked to power structures. She argues that the way it is made involves extracting resources from people and the planet, and the way it is used reflects the beliefs and biases of those who wield it. Only when we come to terms with this, says Crawford, will we be able to chart a just and sustainable future with AI. In this interview from The Observer Crawford discusses these issues and says: “AI is neither artificial nor intelligent.” Why this is important: As data scientists, we are extremely familiar with the use of AI, so much so that we may often take it for granted. Thinkers such as Crawford offer a unique perspective that causes us to evaluate our industry and the products it creates, in a different way. [Click here to read on!]( [The Latest Trends Data Scientists Should Be Aware Of]( In brief: As a data person, you stand at the forefront of the digital revolution. While you must ensure your deep technical fitness and progress, it is also vital that you are not losing track of the big picture. Therefore, it’s imperative that you should keep abreast of the technology trends and be aware of how they may potentially impact your work. By doing this, you can ensure that you can stay relevant in the future of data science, ML, and AI job market. As such, this list of the ten latest trends that data scientists should be familiar with offers interesting insights into the current state of the industry. Highlighted trends include MLOps, contrastive learning, transformers, carbon footprint, the monetary cost of deep learning, graphs, integrated toolsets that are easier to use, models that explain other models, contextualized word embeddings, and small data. Why this is important: Trends are often considered to be particularly relevant to entry-level data scientists, but experienced practitioners should also ensure that their knowledge is current and plentiful. [Click here to discover more!]( [Europe’s AI Laws Draw Criticism from Digital Rights Groups]( In brief: More than 175 civil rights groups, activists, and researchers from across the world are calling for a global ban on facial recognition and remote biometric systems. An open letter highlights human rights abuses enabled by the use of surveillance technology in countries such as China, Russia, and Myanmar. The document, signed by groups and individuals including Amnesty International and the Internet Freedom Foundation, demands a halt in all public investment in uses of technologies enabling mass surveillance and advocates for their prohibition in all public spaces. The coalition was convened by the digital rights group Access Now, and the letter was drafted by European Digital Rights, Human Rights Watch and Instituto Brasileiro de Defesa do Consumidor, among others. Signatories include Big Brother Watch and Privacy International. The letter was written in response to concerns that the EU’s artificial intelligence bill could allow for widespread facial recognition beyond Europe’s borders. Why this is important: As we’ve covered previously, the AI bill has been controversial due to the fact that it restricts the practice of using facial recognition software but stops short of a complete ban. This letter shows that this is an issue that will not disappear, with international attention being drawn to Europe. [Click here to see the full picture!]( [Lessons To Be Learned from Major Internet Outage]( In brief: A number of major websites, including the UK government site, have been hit by an outage at global website hosting service. For around an hour on Tuesday morning, those logging into a raft of other sites were faced with a message saying "503 Service Unavailable" or similar. Sites affected included the UK’s gov.uk; news outlets The Guardian, Financial Times, Independent, New York Times, and Le Monde; as well as Reddit, shopping site eBay, and streaming platform Twitch. There had also been reports of other sites being down including Amazon, PayPal, CNN, and Spotify. An unexplained configuration error at a single infrastructure provider, Fastly, which handles 10% of the world’s internet traffic, was enough to render the major websites and services inoperable. The affected sites all used Fastly as a content delivery network (CDN), a service intended to provide greater reliability and performance for heavily trafficked websites. Why this is important: Although this story may initially appear to have little to do with data science, it offers important lessons on what happens when one cloud-based service is relied upon exclusively. This case proves that internet services are too centralised and lack resilience and should serve as a wake-up call to all of us. [Click here to find out more!]( [SuperDataScience podcast]( In this week's [SuperDataScience Podcast](, Sidney joins us to discuss her computer science studies at Make School, building out Make School’s data track, her interest in AI for healthcare, and some of her tips and strategies for becoming a successful early-career data scientist. --------------------------------------------------------------- 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? Are you either a data professional or an executive trying to implement AI technologies in your organization? We’re sure you’re always exploring some upskilling opportunities for yourself or your team. Please share your experience with corporate and self-education [right here](. 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