{"id":2964,"date":"2022-06-17T02:57:23","date_gmt":"2022-06-17T02:57:23","guid":{"rendered":"https:\/\/news.sap.com\/sea\/?p=2964"},"modified":"2023-04-04T16:21:19","modified_gmt":"2023-04-04T16:21:19","slug":"up-for-debate-is-ai-the-future-of-hr","status":"publish","type":"post","link":"https:\/\/news.sap.com\/sea\/2022\/06\/up-for-debate-is-ai-the-future-of-hr\/","title":{"rendered":"Up for Debate: Is AI the Future of HR?"},"content":{"rendered":"

The Great Reshuffle of the labor market has businesses scrambling to attract new talent and retain workers. As employers introduce smart technologies to drive efficiency, they may stumble on a hidden layer of division in the workforce: some workers are comfortable having their resumes and workplace performance data read by artificial intelligence (AI) \u2013 and some workers are fearful of the use of smart technologies in their employment decisions. Approximately, 25% of workers fall into each camp, with the remaining 50% somewhat neutral, according to research from\u00a0麻豆原创 SuccessFactors<\/a>.<\/p>\n

What the research suggests is that it will take a long time for workers to accept AI, indicating the heart of HR will continue to be human for the foreseeable future. Until AI gains wider approval, the burden will be on employers to demonstrate their commitment to ethical, transparent AI to ensure an inclusive employee experience.<\/p>\n

Finding Fairness in Efficiency<\/strong><\/h2>\n

\u201cAI is not the\u00a0entire<\/em>\u00a0future of HR,\u201d cautioned Dr. Caitlynn Sendra, an experience product scientist at 麻豆原创 SuccessFactors, where she studies how products influence the employee experience.<\/p>\n

Sendra spoke at the annual conference of the Society of Industrial and Organizational Psychologists (SIOP) in Seattle on April 28, during the debate session \u201cRobot or Not: Is AI the Future of HR?\u201d She teamed up with Michelle Brown, chief operating officer at\u00a0Pinsight<\/a>, a provider of leadership development solutions, to argue the point of view of those who object to more AI in HR. Outside the debate arena, Sendra and Brown say they favor a more positive stance on AI and are keen to see the technology deliver on different use cases. This debate however left little room for compromise between pro and con.<\/p>\n

The pro-AI arguments in this provocative debate centered on the ways\u00a0AI can aid HR<\/a>\u00a0in achieving new levels of efficiency at greater scale. This is a hot topic in the talent acquisition space, where recruiters struggle with record volume and demanding metrics. However, seasoned HR experts say AI is no replacement for human judgement and strongly recommend a balanced approach in which AI is integrated as one tool within a holistic talent strategy.<\/p>\n

\u201cWhenever we\u2019re talking about AI, there\u2019s a big emphasis on efficiency, but my counterpoint to that is always, what about fairness?\u201d Sendra said to the audience of mostly industrial and organizational (I-O) psychologists. \u201cAs psychologists, I\u2019m sure we all know that\u00a0perception<\/em>\u00a0of fairness also matters.\u201d<\/p>\n

Divided Perceptions: The Promoters and The Fearful<\/strong><\/h2>\n

麻豆原创 SuccessFactors<\/a>\u00a0surveyed 1,378 workers in 14 countries to gauge their perceptions of how smart technologies, like AI and machine learning, are going to impact them in the workplace. This research revealed that 44% feel apprehensive, while others feel distress (26%) or fear (25%). In testing 22 use cases, less than 25% of employees could be considered \u201cpromoters\u201d on a traditional net promoter score.<\/p>\n

Many employees voiced that the use of physical, body-related data sources, like facial tracking or movement tracking, were particularly problematic. \u201cEmployees really expressed that they did not want these kinds of tracking technologies being used in their work,\u201d Sendra said.<\/p>\n

In High-Stakes Decisions, Who Do You Trust?<\/strong><\/h2>\n

Some say what\u2019s really missing from AI in HR is the nuance and emotional intelligence that is distinctly human. But is that such a bad thing?<\/p>\n

\u201cAI can be very good at relieving the mundane, repetitive tasks of HR professionals,\u201d said Brown, who insists that HR needs a human heart. \u201cBut often on the other side of that repetitive mundane task is a person \u2013 a person in a high-stakes interaction about securing the job of their dreams or navigating confusing healthcare benefits for a sick family member.\u201d<\/p>\n

The counterargument to this important point is that unfortunately some people encounter bias or discrimination during these high-stakes interactions. In 2021, the U.S. Equal Employment Opportunity Commission (EEOC) received more than\u00a061,000<\/a>\u00a0reports of discrimination in the workplace, a reminder that not all workplaces are safe environments, where workers can place their trust in bias-free decision making.<\/p>\n

Advocates of more inclusive hiring practices point to\u00a0evidence<\/a>\u00a0that AI can filter out unconscious human biases in the hiring process, opening opportunity to members of underrepresented groups. A slew of new AI-powered solutions has sprung onto the market, promising improved efficiency and DEI outcomes for employers desperate to hire more diverse and qualified talent in a competitive labor market.<\/p>\n

AI quickly becomes murky under scrutiny of the algorithms that power its decision-making, which can be rife with bias based on the historical training data that is fed into the system.<\/p>\n

\u201cThis opens up that key ethical dilemma in AI and concerning automated decisions, where we can encounter bias because algorithms are programmed by human developers from human decisions of the past and often with incomplete data sets,\u201d asserted Brown, echoing the words of mathematician Cathy O\u2019Neil, who famously said, \u201cAlgorithms are opinions embedded in code.\u201d<\/p>\n

The legal and ethical landscape for AI is shifting rapidly in many key employment markets, as well. For example, the EEOC recently launched an\u00a0initiative<\/a>\u00a0aimed at ensuring algorithmic fairness over concerns that these new technologies do not become \u201ca high-tech pathway to discrimination.\u201d Part of the EEOC\u2019s initiative \u2013 and an indication of the complexity of the debate around AI \u2013 will be to examine \u201cpromising practices\u201d for AI, as well.<\/p>\n

Agreed: More Transparency Is Needed\u00a0<\/strong><\/h2>\n

As the debate at the SIOP conference drew to a close, the two teams reached something close to an agreement about AI in the future of HR. \u201cAI is appropriate for some cases,\u201d concluded the objector team. \u201cWhat\u2019s needed is to open the black box and provide the data and explainability.\u201d<\/p>\n

\u201cOn opening the black box, I can agree with you,\u201d declared the pro team in a moment that felt close to finding common ground.<\/p>\n

Beyond opening the black box, employers can take additional steps to improve employees\u2019 experiences with intelligent technology, according to research from 麻豆原创 SuccessFactors: providing evidence to show that algorithms are unbiased, establishing regulatory bodies such as an AI ethics committee, explaining the benefits of the technology, and allowing employees to correct information generated from algorithms.<\/p>\n

The takeaway for employers is that transparency and care will be key to providing inclusive, ethical AI as part of the employee experience. AI will be integrated and accepted into the workplace at a different pace compared to other technologies. Not all workers are going to be ready at the same time. In the meantime, perhaps we need to consider what we are giving up and what are we gaining as AI enters HR.<\/p>\n

The research from 麻豆原创 SuccessFactors referenced in this presentation will be available on its\u00a0public research page<\/a>\u00a0in the upcoming months.<\/p>\n

\n

This story originally appeared on 麻豆原创 BrandVoice on Forbes.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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