Digital Transformation and Technology

Perspectives from a HR tech expert on the top three discussions that emerged from our recent CIPD Hackathon 2030 under the theme of digital transformation and technology for HR.

People Analytics

Perspectives from a HR tech expert on the top three discussions that emerged from our recent CIPD Hackathon 2030 under the theme of digital transformation and technology in the People Profession.

As a Facilitator for the global and virtual CIPD Hackathon in August I connected with people from all over the world, sharing ideas about how technology is changing our business, our function, and ourselves. While online conversations ranged widely and touched most HR topics there were three main areas I saw emerge under the digital transformation and technology theme.

1.  Evidence-based practice and psychologically sound technology
A heavy and somewhat polarising issue, participants debated the relevance of HR practices in the light of today’s scientific knowledge, and how we could merge it with the digital transformation of the HR function. Evidence Based Management (EBM) within HR was covered as was the need for scientific robustness in HR technological tools, from both the psychology and technology perspectives.


Evidence Based Practitioners were calling out that many of our current HR practices, digitised or not, are inconsistent with current scientific recommendations. For many of us in HR this is no surprise. There are many policies and practices found and maintained in workplaces today that are not scientifically sound, and in some cases scientific evidence shows their impact to be contrary to the desired outcome. Some Hackathoners said that there is little point maintaining processes and approaches that would not achieve the desired results and, in some cases, are counterproductive. Others pointed out that practices should be changed over time instead, as uprooting common practices simply because they lack scientific robustness was too disruptive. Both arguments have merit. Accepting that some HR approaches, practices, and policies are scientifically unable to produce the intended result or outcome, then ‘when’ rather than ‘if’ they are changed becomes the focus.

Digital transformation provides the opportunity to change HR approaches, practices, and policies. However, to benefit from the opportunity, we need to choose technology tools that are scientifically robust and reliable from both psychological and technological perspectives. This is difficult because many technology tools on the market would fail to meet that standard. They make claims that only sound possible because of the oft-vaunted illustrious claims by vendors and others about what their tool can achieve in the workplace. HR Technology is where psychology and technology meet head-on. Good HR technology meets both scientific standards.


Transforming HR to a digital and evidence-based function requires people who can identify sound scientific practices and probe HR technology vendors to ascertain the scientific basis (psychologically and technologically) of their products.

2.  Artificial Intelligence and Bias
When Artificial Intelligence is discussed in HR circles the topic of bias is not far behind. It was interesting to see through the conversations that some people had an awareness of what was causing Artificial Intelligence powered tools to generate biased results, but understanding was far from widespread. Bias, like Diversity and Inclusion, are important topics for HR. While HR ramps up the adoption of Artificial Intelligence within the function, a thorough understanding is needed of how and why bias exists in the tools.


Broadly, there are three areas that can result in Artificial Intelligence (AI) tools producing biased results.
a. Training Dataset - The dataset the AI model is trained on is biased. All AI models must be taught before they can be useful, if they are taught on biased data then the model has learned the bias in the training dataset. Most of us never ask an AI vendor about the source or composition of the training dataset. If the model has been trained on a biased dataset, vendors should be able to tell you what they did to adjust and correct the model to mitigate that bias.


b. Algorithm – When algorithms are written they capture the biases of the person or people creating them. Algorithmic bias is often attributed to the dominance of white males in the field, hence the drive to increase the diversity of people in this job. In some circles, the idea of addressing bias at the algorithmic level under the principles of affirmative action is being discussed and explored.


c. Our data – We are often unaware of the biases hidden in our own data. AI learns from its own output, so even a small bias in our data is magnified over time. Our data often represents the collective conscious and unconscious biases within our organisation, created when bias creeps in through everyday decisions made by employees. To avoid the AI learning and amplifying the bias, we need to ensure there are humans-in-loop to monitor output and make appropriate adjustments.

3.  HR people know they need to reskill


Most people who entered the Human Resources profession a decade ago did not consider it necessary to learn about technology or data and analytics. Today, if an HR professional wants to remain employable over the next 5-10 years, there’s little choice; reskilling in those areas is critical.


Most Hackathoners accepted the need to reskill, and a few were excited by the prospect. The conversation was spurred by a report by the Cognizant Centre For The Future of Work with key findings republished by Harvard Business Review during the Hackathon. The report, 21 HR Jobs of the Future, outlined new roles arising over the next 5-10 years. Most HR professionals commenting in the Hackathon recognised that they are not suitably skilled to perform most of those roles, though a small selection of tasks were already appearing in existing roles today.


During the Hackathon the idea that the jobs in the report are not really HR jobs was raised, and that HR should be hiring from different pools of talent such as IT. However, this was counter-balanced by people saying that if HR people cannot take those jobs, where will HR people go?

Considering the first two areas under the digital transformation and technology theme, there is no doubt that HR practitioners who wish to remain employable must reskill and learn about technology.

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