Automation can make recruitment more human, report reveals
As the talent acquisition transformation accelerates demand for recruitment automation, with 55% of companies increasing investment in recruitment automation this year, concerns about automation removing the human element from the process remains rife.
But, according to new insight from Aptitude Research, the opposite ca n be true.
Recruitment automation accelerating
Much is being made of the ability of artificial intelligence (AI) to significantly transform Human Resources and in particular the recruitment process with the use of auto-screening or machine-learning software enabling firms to shortlist candidates, without reading CVs.
And while these companies recognise that the use of AI technology to automate the recruitment process can improve efficiency, lift administrative burden, reduce costs, and enable data-driven decisions, there are concerns that the technology could also remove the ‘human’ aspect of human resources.
The opposite can be true, however. That's according to research and a report from Aptitude Research, titled Recruitment Automation with Humanity, which focuses on recruitment automation through the lens of the candidate.
AI can improve human element of recruitment
The research, sponsored by Australian automation company PredictiveHive, reveals that when you shift the focus in automated Talent Acquisition from employer-driven to a candidate-first, it is possible to reduce bias in hiring and improve the overall human element of recruitment.
Humanistic automation can create personal connection at scale, and work to reduce bias, finds the research, something no other technology or even human-centred solution can deliver. This means that companies can communicate in a meaningful and inclusive way and build trust between candidates and employers.
“The misperception that candidates do not want automation and prefer to keep the current talent acquisition is one of the most significant misperceptions in talent acquisition,” states Aptitude's CEO, Madeline Laurano.
Laurano argues that what candidates want most is a fair recruitment process and consistency in communication and that automation can support all of these initiatives and “enhance the humanity of the experience”.
4 ways to humanise recruitment automation
There are four main ways that talent acquisition can be made more human with automation when the candidate is the focus, rather than simply moving candidates through the process:
- Automation can understand what candidates want: AI considers the unique expectations and experiences of candidates and adapts to them as it learns. Collecting feedback about the recruitment experience and continually improving the candidate journey can help candidates feel connected and heard.
- The correct data can interrupt bias early in the process: By creating a consistent and fair experience for candidates early in the process, and not relying on CV data as the determinate of job suitability, companies are more successful at reducing bias and increasing inclusivity.
- Trust can be built through transparent data: Both employers and candidates need to trust the data and methodologies for the technology that they are using, something that can be achieved through transparency. Companies looking at automation should consider providers that will partner with them and provide transparency.
- Provide feedback to every candidate: Though natural language processing every candidate receives personalised feedback and messaging. Leaving unsuccessful candidates feedback they can use for future job searches is empowering and a big leap from 'ghosting' or a standard rejection email.
Chinese Firm Taigusys Launches Emotion-Recognition System
In a detailed investigative report, the Guardian reported that Chinese tech company Taigusys can now monitor facial expressions. The company claims that it can track fake smiles, chart genuine emotions, and help police curtail security threats. ‘Ordinary people here in China aren’t happy about this technology, but they have no choice. If the police say there have to be cameras in a community, people will just have to live with it’, said Chen Wei, company founder and chairman. ‘There’s always that demand, and we’re here to fulfil it’.
Who Will Use the Data?
As of right now, the emotion-recognition market is supposed to be worth US$36bn by 2023—which hints at rapid global adoption. Taigusys counts Huawei, China Mobile, China Unicom, and PetroChina among its 36 clients, but none of them has yet revealed if they’ve purchased the new AI. In addition, Taigusys will likely implement the technology in Chinese prisons, schools, and nursing homes.
It’s not likely that emotion-recognition AI will stay within the realm of private enterprise. President Xi Jinping has promoted ‘positive energy’ among citizens and intimated that negative expressions are no good for a healthy society. If the Chinese central government continues to gain control over private companies’ tech data, national officials could use emotional data for ideological purposes—and target ‘unhappy’ or ‘suspicious’ citizens.
How Does It Work?
Taigusys’s AI will track facial muscle movements, body motions, and other biometric data to infer how a person is feeling, collecting massive amounts of personal data for machine learning purposes. If an individual displays too much negative emotion, the platform can recommend him or her for what’s termed ‘emotional support’—and what may end up being much worse.
Can We Really Detect Human Emotions?
This is still up for debate, but many critics say no. Psychologists still debate whether human emotions can be separated into basic emotions such as fear, joy, and surprise across cultures or whether something more complex is at stake. Many claim that AI emotion-reading technology is not only unethical but inaccurate since facial expressions don’t necessarily indicate someone’s true emotional state.
In addition, Taigusys’s facial tracking system could promote racial bias. One of the company’s systems classes faces as ‘yellow, white, or black’; another distinguishes between Uyghur and Han Chinese; and sometimes, the technology picks up certain ethnic features better than others.
Is China the Only One?
Not a chance. Other countries have also tried to decode and use emotions. In 2007, the U.S. Transportation Security Administration (TSA) launched a heavily contested training programme (SPOT) that taught airport personnel to monitor passengers for signs of stress, deception, and fear. But China as a nation rarely discusses bias, and as a result, its AI-based discrimination could be more dangerous.
‘That Chinese conceptions of race are going to be built into technology and exported to other parts of the world is troubling, particularly since there isn’t the kind of critical discourse [about racism and ethnicity in China] that we’re having in the United States’, said Shazeda Ahmed, an AI researcher at New York University (NYU).
Taigusys’s founder points out, on the other hand, that its system can help prevent tragic violence, citing a 2020 stabbing of 41 people in Guangxi Province. Yet top academics remain unconvinced. As Sandra Wachter, associate professor and senior research fellow at the University of Oxford’s Internet Institute, said: ‘[If this continues], we will see a clash with fundamental human rights, such as free expression and the right to privacy’.