I
n a panel discussion at the CIPD conference, legal and government experts took part in a robust discussion about the benefits and pitfalls of AI in recruitment. Panellists explored the
global acceleration of the integration of AI in HR and recruitment processes. Organisations are currently debating and testing
three concerns: how to take full advantage of powerful AI systems; where AI is best placed to provide the most value; and how to manage its use, staying mindful of the legal and ethical dilemmas it presents. This is particularly difficult to do without clear
guidance around ethical standards, something which governments themselves are grappling with. What’s more, while you may think your current hiring process is AI-free, this may not be the case. Many recruitment tools use an element of AI in the job matching or screening process. So, could AI be a positive force or a serious legal danger
within the world of work? How can we deal with concerns around data privacy and ethics? Do AI algorithms perpetuate bias and discrimination? How could AI support efficiency and innovation at work? We look at some of the positive impacts of using AI strategically in the recruitment process and the legal pitfalls.
AI IN RECRUITMENT – CAN IT DELIVER HIGH VOLUME EFFICIENCY? Nikki Sun, research and programme manager at Oxford Martin AI Governance Initiative, has a decade of experience working at the intersection of journalism, public policy and emerging technologies. The Oxford Martin School is a research and policy unit based in the social sciences division of the University of Oxford. Its research is used to support decision-makers from industry, government and civil society mitigate AI’s challenges and to realise its benefits. Her previous research has studied the impact of AI on
employment and labour in China and how AI is shifting the power imbalance between workers and employers. She described the use of AI in mass recruitment for roles like assembly line workers and delivery drivers in China. In her research on the Chinese workplace, she found that AI is often preferred for roles with standard job descriptions and large volumes of applicants. “When dealing with thousands of applications, for
example assembly line workers in factories and delivery drivers, AI is definitely more preferable there because usually the job description is very standard and they just check whether applicants meet certain standards and then hire them,” she explained. “In terms of senior roles or in the field of highly
skilled work, people tend to use human HR in dealing with the applicants. Although companies are trying to do more with AI in more senior roles as well, we haven’t really seen much progress. In terms of the decision- making process in evaluation and promotion, or pay rises, companies are more comfortable to have human HR as a final reviewer and decision maker.”
THE LEGAL LANDSCAPE: VARYING REGULATORY APPROACHES The legal regulation of AI in HR and recruitment varies by region. The EU sets rigorous standards under the EU AI Act, which categorises recruitment and employee management systems as “high-risk” areas. This classification imposes strict obligations on companies that use AI for hiring, promotions and performance monitoring. For instance, under the EU AI Act, companies must ensure transparency, monitor AI input data and notify workers if these systems are in place. Additionally, public sector employers are subject to more stringent rules. The UK, in contrast, has adopted a more flexible “principles-based approach” as outlined in its White Paper, focusing on regulating AI by relying on existing legal frameworks, like the Equality Act and GDPR. These existing laws, which address discrimination, data protection and consent, already apply to employment contexts, but cover areas where AI’s role is expanding. Companies operating in both regions must ensure compliance with these regulations to avoid liabilities. Furat Ashraf is a partner at Bird & Bird in the
international HR services group in London and is an employment lawyer supporting clients on the full spectrum of contentious and non-contentious employment law issues across EMEA and APAC. Acting for a broad range of clients from global financial institutions to multinational corporates, her experience includes drafting and negotiating settlement agreements and employment contracts, reviewing and updating employment policies and handbooks, and advising on the employment aspects of large cross-border corporate transactions. She explained to the panel, which was chaired by
Hayfa Mohdzaini, a senior policy and practice adviser – technology at the CIPD, that AI legislation is still being debated and that there was “quite a spectrum” between the EU, UK and US when examining the approaches that different regions and countries are taking. “This covers recruitment and selection, decisions affecting work relationships, promotion, termination, and any kind of monitoring of performance and behaviour,” she said. The EU AI Act will have extra territorial effects,
meaning that if you are a UK business that sells products into the EU, then you will be bound by those regulations. It also specifies the need for a degree of human oversight, strict obligations in relation to data input into certain AI systems and the obligation to notify workers’ representatives and affected workers. “When you look at the UK position, it really ties
back to the White Paper produced by the previous government, which was very focused on using a principles-based approach,” she said. “One of the things that people often overlook is that
AI is another technology and we have a lot of existing laws, particularly in the employment context, that HR practitioners will be familiar with, and which regulate how you use technology when it comes to the workforce. “For example, the Equality Act is a good example of
49
GLOBAL LEADERSHIP SUPPLEMENT
AI RECRUITMENT
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86
