Employees Hired & Fired By Algorithm
Uploaded on 2021-04-05 in TECHNOLOGY-Key Areas-Artificial Intelligence, FREE TO VIEW
The rising prominence of Artificial Intelligence (AI) in the workplace is challenging existing professional roles and skills. To date, AI algorithms have proven useful for handling large quantities of data and image processing, but recent advances have made it possible to create AI systems that interact with humans. Indeed, many firms already use an automated system with no human oversight in the first stage of the hiring process, to narrow the field. AI software is now used in the initial recruitment processes of a number of multinational companies, including McDonald's, JP Morgan, PWC, and Kraft Heinz. Only after the initial AI - driven selection process will there be any personal contact involving a human recruiter.
“We stand on the brink of a technological revolution that will fundamentally alter the way we live, work, and relate to one another... In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before.,” according to the British Trade Union Congress (TUC).
Many workplaces already use automated decision making for simple tasks. For example, Uber assigns driving jobs to its drivers automatically, by computer, and Amazon is known to use AI monitoring systems to watch its staff in its warehouses. One provider of AI recruitment software is HireVue which offers an AI system that records videos of job applicants answering interview questions via their laptop.
But as AI becomes more sophisticated, the fear is that it will be entrusted with more serious, high-risk decisions, such as analysing those performance metrics to figure out who should be first in line for promotion, or being dismissed. That can happen even when a human is involved, a TUC report warns, thanks to automated decision making.
The TUC is saying that workers could be “hired and fired by algorithm” and new legal protections were needed, waring of “huge gaps” in UK employment law over the use of AI in the workplace.
Among changes the TUC is calling for is a legal right to have any “high-risk” decision reviewed by a human. TUC general secretary Frances O’Grady said the use of AI at work stood at “a fork in the road... 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,” she said.
The TUC’s report, written with the aid of employment rights lawyers and the AI Law Consultancy, argues that the law has failed to stay abreast of quick progress in AI in recent years. The Report is split into three parts:
- An outline of the nature of new AI technologies deployed in the workplace and the applicable legal framework before setting out “red lines”beyond which AI systems should not be used.
- An assessment based on case studies of the effectiveness of current legal frameworks to control and protects workers from the use of AI in the workplace.
- Specifiic recommendations that should underpin the future actions of legislators, regulators and the trade union movement.
The TUC is calling for Changes to UK law to protect against discrimination by algorithm. In particular:
- The legal right to have a human review decisions.
- An obligation on employers to consult unions on the use of “high risk” or “intrusive” AI at work,
- A legal right to “switch off” from work and not be expected to answer calls or emails
The TUC claim that discrimination by algorithm has been well-documented in recent years, often as an unintentional side-effect of using systems that fail to account for racial bias. “AI is progressively gaining the ability to perform tasks typically carried out by humans and stresses, therefore, the need to establish adequate safeguards, including design systems with human-in-the-loop control and review processes, transparency, accountability and verification of AI decision-making …” it , concludes.
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