Machine Human collaboration path starts with defining guidelines

Humans are in the driving seat, so get to decide the rules of the collaboration setting. However, as the arrangement evolves, machines may also start taking autonomous execution and restricts flexibility.  

   

Overarching principles and design guidelines 

1. At all times, HR has to be aligned with business goals and organisational stated values.  Talent is a key strategic asset, and its acquisition, growth, deployment for business goals is the core non-negotiable accountability.
2. Building a positive work environment, with shred sense of equity and fairness to maximize productivity and satisfaction remains core.  
3. Accountability towards Legal, ethical, and policy compliance across geographies, especially in multi-sector environments, is non-negotiable.
4. All decisions recommended by Machines (AI) should be explainable and may require human review — especially in critical or ethical contexts. 
5. There should be Intelligence-Led Decisioning ie decisions to be informed by predictive insights, prescriptive analytics, and scenario modeling provided by machines.
6. Agent-Led Execution of the repetitive and logic-based tasks. There is openness to redefine the present processes, workflows and decision rights to make tasks amenable to agent led delivery.  
7. Continually strive towards hyper-personalisation, based on profile, experience, interest, intent, and opportunity capture
8. High standards of Digital Ethics and Transparency supported by Clearly define data boundaries, model transparency, and ethical standards for use of employee data and AI-led decisions
9. Modular & Platform-Based Architecture, allowing for easy integrations with other systems and introduce agents. 
10. Reimagination and experimentation approach supported by feedback loops to continue evolving and moving on the evolution trajectory
11. Pace and realm of transition to accommodate employee's adaption challenges, keeping intact trust while managing negative associations like privacy concerns, algorithimic bias or over de-humanisation. 
12. There is always human escalation path available for any automated processes.      

Translating these principles and guidelines into action would require setting up new institutional structures like joint ethics and governance committees and cross functional teams, enhanced role of CHRO, CDOs and other leaders.  

Besides, this would require reimagining of the role of HR workforce as they share their work with machines going forward.       

Handing over to Machines : The Why and why-not Question?

Like all dimensions of work, the conventional work done by Human resource professional is also under scanner and expected to be given to, fully or partially, to machines.  

The prime motivation is to leverage the tireless energy, unbiased application of decision rules, immense retrieval and computing capabilities and NLP based interactions of new set of digital technologies (RPA, AI ML, Chatbot, Agentic-AI) for the good of employee, managers and organisation.  

The Why-Machine question?

The key motives for introducing machine power in HR context hovers around the following:

1 If Talent is the strategic asset, then machines help identify, acquire and deploy this asset better, and more efficiently. It can provide fitment score. predict the performance outcome, attrition risk and often provide the hidden talent option that is hidden in the remote work location.    

2 If employee experience at workplace is to be as good and personalised as at market-place, we can emulate same solutions for validation, interaction, recommendations and transactions, chatbots for example.    

3 If trust, transparency and auditability behind routine transactions are important, machines deliver better and at scale, using RPA as a disciplined agent.   

4 If machine releases cognitive capacity of the workforce, by taking over routine and rule-based decisions, why not? And machine capacity to adjust to scale is far more than of workforce. 

5  If the outfall of mistake by machine is manageable and not disproportionate from ethical, reputational and economics consideration, lets go ahead.   

In recognition of the above, over 70% big corporations are using machines in HR for some purpose or other.  

The Why-Human question?

At the same-time, need for putting Human in the loop is often felt: 

1 If the decision or action would create negative consequence, (say disciplinary action, dismissal), human judgement is warranted?

2 If there is less confidence in defending explainability of decisions or actions by machines to externl party, keep Human in the loop

3 If the empathy and emotions are as important as the content of the interaction for employee satisfaction, oblige

4 If the reliability of the data sets driving transcations and decisions are a suspect, let humans decide

5 If the decisions require case-2-case considerations with high level of contextual and subjective discretion, humans are not replaceable.

Moving work from humans to machines has to be a deliberative, and structured transition, ensuring coordinated readiness around policies, processes, technology and people dimensions, to make it seamless and well recived by stakeholders.