People function role in navigating AI controversy: Lessons from Uber's AI facial recognition and discrimination claims

The rapid advancement and integration of Artificial Intelligence (AI) technology into various aspects of our lives has been met with both excitement and apprehension. One such instance is Uber’s adoption of AI-driven facial recognition for driver verification. While this move was intended to enhance security and streamline operations, it has become embroiled in controversy due to allegations of racial discrimination against drivers. This emerging issue underscores the complex interplay between technology, fairness, and the evolving landscape of employment practices. In this blog post, HR Optimisation delves into the details of this case and explore the implications it holds for the wider adoption of AI in workplaces and the role of People teams in engaging in the debate.

The Uber Case at a Glance:

Uber, known for its innovative approach to employment practices, introduced facial recognition software in April 2020 to authenticate the identity of its drivers. However, this move has been met with claims that the technology discriminates against drivers based on their race. Two separate unions have taken up cases against Uber, sparking a legal debate that draws attention to the role of AI in modern workplaces.

Facial Recognition in Practice:

Uber’s “Real Time ID check,” developed in collaboration with Microsoft, mandates drivers to submit a photograph of themselves before gaining access to the app for work purposes. While this feature was introduced to ensure passenger safety and driver accountability, concerns have arisen regarding the accuracy of face recognition algorithms, particularly when it comes to individuals of colour. Research from the US National Institute of Standards and Technology has shown disparities in misidentification rates among different racial groups, with higher error rates for African American and Asian individuals. Moreover, regulatory bodies like the Equality and Human Rights Commission in the UK have raised questions about the oversight of such technologies.

Consequences for Drivers:

Drivers who are unable to be verified through the app’s facial recognition system face serious repercussions. If the system fails to recognise the driver’s face, access to the app is suspended for 24 hours, impacting their ability to work. Repeated failures can lead to account termination and removal from the platform. In severe cases, drivers might even lose their private hire licenses. While the process includes a human review and an appeals mechanism, the consequences of misidentification can still be damaging.

The Legal Claims:

Two prominent cases, Raja v Uber and Manjang v Uber, revolve around claims of indirect racial discrimination due to the app’s inability to accurately identify drivers. In addition, one of the drivers is asserting claims of harassment and victimisation based on the same grounds. Indirect discrimination occurs when a seemingly neutral rule or practice disproportionately affects individuals with specific protected characteristics. The cases underscore the need for employers to objectively justify such practices.

Implications and Learning Points:

As these cases remain ongoing, they highlight the contemporary challenges that employers face as they integrate technology into their operations. Generative AI when trained on massive data sets learns how to assimilate and then create new content in the form of images, text, audio and video based on that training. While AI can undoubtedly enhance efficiency and decision-making, it must be guided by safeguards to ensure fairness and compliance. This controversy isn’t confined to Uber alone; AI’s increasing role in recruitment and decision-making processes also raises concerns. From potential privacy implications to the prohibition of automated decision-making without human intervention under data protection laws, the ramifications of AI adoption are vast.

GPT-4, the latest variant from OpenAI released in March, is already proving itself to exhibit human level performance on various professional and academic benchmarks – more recently it also prompted more than 1,000 people, including AI experts and Elon Musk to sign a letter calling for a six-month pause on further training or development of these tools until “we are confident that their effects will be positive and their risks will be manageable”. The letter cited risks to humanity and society, including the spread of misinformation and displacement of jobs. As well as the significant aforementioned risks in how AI could exacerbate division of opportunity, inbuilt bias and infringement on privacy; a recent report by Goldman Sachs estimated the equivalent of 300 million jobs could be replaced – or 1/4 of all work tasks in the US and Europe. For HR this means we must keep abreast of, and prepare for these challenges and the potential need for organisational restructures in the imminent future. On the positive, AI could be transformative in increasing human productivity and carrying out many administrative or support tasks – perhaps this is what will enable a future of a 4 day working week and higher pay?

Conclusion:

The clash between Uber’s AI facial recognition technology and allegations of racial discrimination underscores the intricate relationship between innovation and ethics in the workplace. This case serves as a cautionary tale for organisations embracing AI solutions, urging them to strike a delicate balance between technological advancement and equitable treatment. As we continue to embrace AI’s transformative potential, it becomes imperative to ensure that its implementation aligns with principles of fairness, equality, and legal compliance.

These changes all signal an important need for people departments to engage and play a central role in how jobs and organisations are shaped, how people develop skills of the future, and how we use these technologies ethically and responsibly. Regulators are struggling to keep pace and the people profession will not be able to rely on pre-determined rules alone – as set out in another recent HR Optimisation article, the EU AI Act is not due until the end of 2023 at the earliest.

If you use AI in your people practices, or are contemplating it and you wish to discuss this advice further please do get in touch on hello@HROptimisation.co.uk

Hannah Powell

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People function role in navigating AI controversy: Lessons from Uber’s AI facial recognition and discrimination claims