Data Science Insider: March 26th, 2021

In this week’s Super Data Science newsletter: Fiverr Adds Data Science Recruiting Category. TUC Warns of Gaps in British Law Over Use of AI. Apple Bought the Most AI Companies From 2016 to 2020. Employees Attribute AI Project Failure to Poor Data Quality. GCHQ Releases 'Toughest Ever Puzzle.' 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. --------------------------------------------------------------- [Fiverr Adds Data Science Recruiting Category]( brief: The latest attempt to address the data science skills gaps comes from Fiverr, a recruiter of freelance talent, which unveiled its first new vertical industry segment since 2012, dedicated to data-related skills and services. The recruiter noted soaring demand for data specialists, especially among small businesses that are steadily embracing data analytics. Fiverr said its new offering includes data science, data analytics, visualization, and processing along with database and data entry categories. In greatest demand are data science skills spanning computer vision, text, and NLP, time-series analysis along with ranking and recommendation systems. Available data science freelancers offered skills ranging from ML using Python to time-series analysis using R. Data analytics specialists offered services ranging from business intelligence to statistical data analysis and data visualization. Geospatial data skills were also heavily represented in the visualization category. Among database specialists, skill sets included different varieties of MySQL and query engine development. Why this is important: This launch is another sign of growing demand for data scientists, showing that requests for data scientists expand beyond large enterprises to include small and medium-sized companies. At the launch, Fiverr cited studies revealing that more than two-thirds of its small businesses are willing to spend more than $10,000 annually on analytics help. [Click here to find out!]( [TUC Warns of Gaps in British Law Over Use of AI]( brief: The Trades Union Congress (TUC) is warning that “huge gaps” exist in British law over the use of AI at work, which will lead to discrimination and unfair treatment of working people. A report produced for the TUC by employment rights from the AI Law Consultancy says the rapid expansion of AI at work is outpacing existing employment law. TUC’s general secretary, Frances O’Grady said: “AI at work could be used to improve productivity and working lives. But it is already being used to make life-changing decisions about people at work – like who gets hired and fired. Without fair rules, the use of AI at work could lead to widespread discrimination and unfair treatment – especially for those in insecure work and the gig economy.” Unless urgent new legal protections are put in place, workers will become increasingly vulnerable and powerless to challenge inhuman forms of AI performance management. Why this is important: This is another example of calls for increased use of ethical AI. The TUC is calling on technology companies, employers and government to support a new set of legal reforms, including a legal duty on employers to consult trade unions on the use of “high-risk” and intrusive forms of AI in the workplace, and a legal right for all workers to have a human review of decisions made by AI systems so they can challenge decisions that are unfair and discriminatory. [Click here to read on!]( [Apple Bought the Most AI Companies From 2016 to 2020]( In brief: Apple was the top acquirer of artificial intelligence companies from 2016 to 2020, beating out companies like Facebook, Google, and Microsoft. According to a new report from GlobalData, from 2016 to 2020 Apple acquired 25 AI firms.The rest of the list of leading AI company buyers included Ireland-based Accenture, Google, Microsoft, and Facebook. Some of the companies that Apple acquired include Silk Labs, Turi, Drive.ai, and Voysis. Apple doesn't disclose any details about its plans for acquisitions, though the AI company purchases are likely to bolster the company's machine learning and Siri-related technologies. GlobalData analyst Nicklas Nilsson said: "Apple has gone on a shopping spree in efforts to catch up with Google (Google Assistant) and Amazon (Alexa). Siri was first on the market, but it consistently ranks below the two in terms of 'smartness,' which is partly why Apple is far behind in smart speaker sales." Why this is important: Growing competition in the AI space has led to an acquisition spree. Apple does not make all of its acquisitions public, so it's possible there are other purchased AI companies that have gone under the radar. [Click here to discover more!]( [Employees Attribute AI Project Failure to Poor Data Quality]( In brief: According to Alation’s latest quarterly State of Data Culture Report, produced in partnership with Wakefield Research, a clear majority of employees (87%) peg data quality issues as the reason their organizations failed to successfully implement AI and ML. The report also found that only 8% of data professionals believe AI is being used across their organizations. For the report, Wakefield conducted a quantitative research study of 300 data and analytics leaders at enterprises with more than 2,500 employees in the US, UK, Germany, Denmark, Sweden, and Norway. The enterprises were polled regarding their progress in establishing a culture of data-driven decision-making and the challenges they continue to face. 87% of professionals say inherent biases in the data being used in their AI systems produce discriminatory results that create compliance risks. Survey-takers pointed to the need for curation and governance, data literacy and understanding, and data from more varied sources. Why this is important: Many firms try to develop AI solutions without having clean, centralised data pools or a strategy for actively managing them. As data scientists, we should be aware that without this critical building block for training AI solutions, the reliability, validity, and business value of any AI solution is likely to be limited. [Click here to see the full picture!]( [GCHQ Releases 'Toughest Ever Puzzle']( In brief: GCHQ has released its "toughest ever puzzle" to commemorate the launch of the new Alan Turing £50 note. The 12-part puzzle on GCHQ’s website is based on imagery and wording from the new note, unveiled by the Bank of England. A further puzzle based on the life of the father of modern computing and AI is contained on the note itself. Printed on the image of a line of ticker tape - denoting the paper tape used by code breakers in Bletchley Park during the Second World War - are a series of ones and zeros. The binary code, once converted into decimal figures, will reveal a date held in special regard by Britain’s modern-day cyberspies. The note also features Turing's words about the rise of machine intelligence: "This is only a foretaste of what is to come, and only the shadow of what is going to be." Why this is important: The puzzles are based on the unique design elements of the new banknote, such as the technical drawings for the British Bombe, the machine designed by Turing to break Enigma-enciphered messages during the war. Historians estimate that the cracking of the Enigma code shortened the war in Europe by around two years and saved hundreds of thousands of lives. GCHQ quizzers say the full challenge could take an experienced puzzler seven hours to complete - are you up to the challenge? [Click here to find out more!]( [SuperDataScience podcast]( In this week's [SuperDataScience Podcast](, Horace Wu joins to discuss his work and hopes for Syntheia, his platform that combs through legal data to augment a lawyer or law firm’s own knowledge and experience to ultimately boost performance. --------------------------------------------------------------- What is the Data Science Insider? 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