Can a Big Tech company be sued in Kenya for alleged abuses at an outsourcing company working on its behalf? That's the question at the heart of two lawsuits that are attempting to set a new precedent in Kenya, which is the prime destination for tech companies looking to farm out digital work to the African continent. The two-year legal battle stems from allegations of human rights violations at an outsourced Meta content moderation facility in Nairobi, where employees hired by a contractor were paid as little as 1.50 per hour to view traumatic content, such as videos of rapes, murders, and war crimes. The suits claim that despite the workers being contracted by an outsourcing company, called Sama, Meta essentially supervised and set the terms for the work, and designed and managed the software required for the task. Both companies deny wrongdoing and Meta has challenged the Kenyan courts' jurisdiction to hear the cases.

Artificial Intelligence ("AI") is often seen as an imminent threat to employment opportunities. According to the OECD, however, AI is more likely to become integrated with certain tasks within a role than result in net job losses. On 23 June 2022, the Expert Group on Future Skills Needs (Irish government advisory group) published a report considering the skills needed in the Irish workforce to benefit from the opportunities presented by AI (the Report). While acknowledging that AI will have an impact on almost every sector of the economy and society, the Report highlighted the current skills gap as the most significant hurdle to AI development in Ireland. The Report finds that due to AI being a "general-purpose technology", it will have a broad impact on the labour market by improving efficiency, reducing costs, improving service offerings, and supporting decision making for firms.

A brief list of our favorite sourcing and recruiting tools, including those that are based on self-learning algorithms. Along with other parts of the business, human resources have also been digitized since the pandemic started. It became obvious that you cannot organize a physical interview with the potential candidates. And that many of them left crowded, expensive cities and went home, to their native towns or countries. Traveling is now open again, but it does not give a guarantee that one can hire new developers or marketers in a traditional way, like it was before the COVID19.

There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.

Science fiction has long imagined a future in which humans constantly interact with robots and intelligent machines. This future is already happening in warehouses and manufacturing businesses. Other workers use virtual or augmented reality as part of their employment training, to assist them in performing their job or to interact with clients. And lots of workers are under automated surveillance from their employers. All that automation yields data that can be used to analyze workers' performance.

The July 2, 1978 issue of the New York Times was the final one the paper sent to print under the linotype process. After decades of relying on Gutenburg printing press-style technology, the newspaper invested in a computerized method that would eliminate the need to physically cast each letter of every page into lead plates for the presses. The automation and digitization of the "hot type" process did not leave linotype operators jobless, however. Those same employees who had run the hot metal typesetting machines were sitting in front of computers the next day, typing stories into a digital format rather than hammering them into place. Asked what the technological upgrade would mean for him personally, one employee responded, "it means I'll have to learn a new process."1

This Employment Law This Week Monthly Rundown features a recap of the biggest employment law trends from 2018 and a look ahead at what's to come in 2019. Specifically, this episode includes the following: 1. #MeToo Movement in the Workplace For employers, 2018 was the year of #MeToo. While the movement began in the fall of 2017, last year, it touched every aspect of employment law--from harassment training to arbitration. Jennifer Gefsky (Member of the Firm, Epstein Becker Green): "I think if the #MeToo movement taught us one thing, it's that employers face significant liability and risk in the event that allegations are made against any employee or supervisor or the highest-level executive at the company." In 2019, we can expect to see more legislative action, particularly in the area of equal pay, where much of the #MeToo focus has shifted.

In this extended interview from Employment Law This Week (Episode 122: Week of June 25, 2018), Michelle Capezza, a Member of the Firm at Epstein Becker Green, explains how recent legal developments have prepared employers for their future workforce, which will include artificial intelligence technologies working alongside human employees. She also discusses the strategies employers should start to consider as artificial intelligence is incorporated into the workplace. Tune in each week for developments that may affect your business. Click here to subscribe by email - select the checkbox next to Employment Law This Week. Please contact [email protected] and mention whether you were at home or working within a corporate network.

Employment Foresight has a number of uses for human resources and legal teams in businesses. The software uses machine learning to identify hidden patterns in judicial rulings, enabling users to navigate difficult areas of employment law and reach more informed decisions around issues such as reasonable notice, employee drug testing, worker classification and exemptions to overtime. The platform collects and analyzes the facts and findings from thousands of previous employment cases, and uses the information to predict how a court might rule in new circumstances. This achieved through statistical methods based on machine learning, focusing in the identification of relationships between different factors like the industrial sector; length of employment; and employee's position. This is to gain an insight into the industrial relations process.

Algorithmic decision making process now affects many aspects of our lives. Standard tools for machine learning, such as classification and regression, are subject to the bias in data, and thus direct application of such off-the-shelf tools could lead to a specific group being unfairly discriminated. Removing sensitive attributes of data does not solve this problem because a \textit{disparate impact} can arise when non-sensitive attributes and sensitive attributes are correlated. Here, we study a fair machine learning algorithm that avoids such a disparate impact when making a decision. Inspired by the two-stage least squares method that is widely used in the field of economics, we propose a two-stage algorithm that removes bias in the training data. The proposed algorithm is conceptually simple. Unlike most of existing fair algorithms that are designed for classification tasks, the proposed method is able to (i) deal with regression tasks, (ii) combine explanatory attributes to remove reverse discrimination, and (iii) deal with numerical sensitive attributes. The performance and fairness of the proposed algorithm are evaluated in simulations with synthetic and real-world datasets.