Artificial Intelligence (“AI”) is scary stuff. To consider that machine learning could out-wit, out-perform and out-last us at work is enough to make us leap to articles like this one.
I doubt that HR professionals are any exception. Here I’d like to encourage us all to take literal heart and I’ll apply some whistle-stop philosophy and a bit of tech explanation to show that we will survive.
Finally, I'll round up 6 suggestions of why the ‘bots won’t beat us yet and a human-being trump card.
I think, therefore I could be a machine
The weakest form of AI means computers performing functions associated with human intelligence. Examples that most of us have heard of are IBM's "Deep Blue" chess player or your new desktop friend, Microsoft's Cortana or Apple's Siri.
But in development now is AI that does not only what we do because we are intelligent, but in the way that we do it too and then more some. Applied generally, one type of machine could act like a human brain for more than one type of human functioning and it would not be limited to accepting the human brain’s conclusions.
“I think, therefore I am”
Rene Descartes' famous reasoning, "Cogito ergo sum" (or "I think, therefore I am") was a conclusion for human-kind that there could be a scientific method which ruled out doubt.
The ultimate doubt for a person (think "The Matrix") is that we exist at all. His thought experiments imagined a demon who could mislead him about anything, except for his own awareness of thought. His thoughts might be wrong, but he knew that he was there as a thinker. “I think, therefore I am.”
Are we facing a new age of reason, where we have to question whether reason means we replace our own reasoning with something that does it better?
Descartes wrote his "Principles of Philosophy" and "The Age of Reason" back in the 17th century, at a time before science as we know it and for sure before the advent of technology. Today I wonder if he might have been just the right thinker to address our question about AI replacing jobs. Are we facing a new age of reason, where we have to question whether reason means we replace our own reasoning with something that does it better?
I think, therefore IBM
The 1988 ad slogan by IBM, "I think, therefore IBM", has since been accredited as one of the most memorable and successful in marketing history. Recently it finds a second coming.
One development behind machine learning is something called a "neurosynaptic chip", which forms the basis for a processor modelled on how brains work and coming close to what brains can do. Potential uses are in robotics, but also in digital assistance to reasoning and decision-making - handling more efficiently, without error or oversight, the complex thinking that we humans do.
IBM are far from alone in working with this. Importantly, the new goal is that the artificially intelligent machine has the same "plasticity" that we do. As it learns, it changes itself. This sounds like horror movies for employment levels.
But here is an amateur thinker’s hypothesis for AI, jobs and HR jobs that presents that movie’s happy ending.
A new Age of Reason?
If thinking is about removing any trace of doubt, providing scientific and empirical analysis and conclusion in a perfectly mechanistic way, then machine learning surely cannot be beaten. We beat it only by agreeing to do so and conceding.
Part 1 of next-generation AI leaves people and machines as happy companions, in all but the most routine of jobs. We can safely assume that some of the "big data" the tech will miss. In HR, today’s tech gives us some good clues as to what may come next for AI. Look at what it currently does well and not so. Making short shrift of volume calculation, searching for needles in haystacks (job applicants?!), synching and linking systems to source constantly updated data is already delivering us great advancement in people management.
Tech is not so great at contextualising, finding exception, bending rules in mitigation or strategising.
But in each case the apparent result or the “insightful” MI must be subject to a rigorous filter as to appropriateness, meaning and value. For example, predictive analytics are still a long way from factoring into every performance case the complete circumstances that we as people understand to be relevant. Or in scanning the online activity of potential hires machine learning might more readily get to flightiness, job dissatisfaction and industry experience than to assessing values or competency fit. Tech is not so great at contextualising, finding exception, bending rules in mitigation or strategising.
But in part 2 of an AI journey ahead, where the data becomes more and more complete, it is harder to be completely certain that our thinking as people allows us to stay ahead. Imagine that those machine tools really did come to learn about all of the data out there and analytical reasoning which was logical. At work where do humans then out-perform?
Remember that when Descartes talked about thought, he included consciousness, awareness and subjectivity. He believed that the duality of mind and body meant that we had a mechanistic, animal functioning - like a machine - which was aside from our soul. In today's context of emerging AI, I wonder if this is a useful notion. Soul is not a word we use much in today’s psychology but we get what it means.
I think, therefore AI: I feel, therefore I am human
Perfect results at work involve feelings, judgments, intuition. These are beyond logical capture.
We noted above how people are best at spotting exception and context – and assessing value and meaning. Potentially even this type of awareness becomes replaceable. Soul does not. The best machine learning could presumably do is to copy what souls seemed to do before or to look for random soul patterns.
So how does soul touch organisations and business?
A New Age of HR
I do not suggest that HR is the only profession with relevance in an age of true artificial intelligence. In a new age of reason, a new age of HR could be one example of 6 uniquely human concepts at work and at play with AI:
- Artistry. Humans understand our expressive enjoyment of what we see, do and use. Consider whether we find things beautiful, elegant, quirky, fun, imaginative or new. Find relevance for reward and motivation, employee engagement, retention, employer branding and learning styles.
- Self-actualisation. A classic and a key concept in acknowledging a striving for empowerment, influence, control. Take away this potential and would we sabotage our machinery before it advanced? HR need to read the talent need to strive and find identity at work.
- Merit in imperfection. Think about how a less than perfect result can sometimes be just the right one when it comes to organisational tactics. Again, HR can find relevance in promoting teamwork and optimum performance, navigating politics, relieving stress.
- Companionship. I deliberately avoid the word “social” because I don’t mean social contact through media or technology platforms. I mean physical and visual awareness of one another to take cues of empathy and respect. Apply this concept to talent management, wellbeing, partnerships. There is also a place for tea and sympathy.
- Deceit. As long as there is a machine-human interface then there is this potential. We could fool tools and we will need an arbiter. Biometrics will have limits. We are brilliant at work-arounds. Perhaps the new specialisms will focus on management technique or business psychology.
- Trump cards. There is often an overwhelming factor that trumps all. I see this a lot with HR systems, where that factor could be the need for change or for no change. Likewise think about the maverick CEO or rogue player. Sometimes the right answer is right because “it just is”. And here humans will hold the trump card for sure.
Notice that the suggestions here do not apply only at strategic level but at the transactional too. In the context of HR, both leadership and operational specialisms can survive supporting advanced machine learning – perhaps in people management skills, care, psychology and talent – and, yes, analysts and HR systems pro’s too.
I think and I feel, therefore I am comfy in cheering on HR technology and AI in the workplace. We can forge ahead in our profession and relax in appreciating that our amateur-ness is quite possibly the HR expert, people team and organisational ace.
About Kate Wadia
Kate’s passion at work is for bridging the gap between technology and people at work, translating for HR professionals the language of HR systems and making meaningful their potential. She believes that success with people technology is through people and that people are the differentiator.
Using simple techniques drawn from HR experience, project management, business psychology and analogy with everyday life, Kate presents and explains how to work well with technology and technology projects in an HR leadership role.
With a background in contrasting private and public sector HR management, Kate developed her thinking in seeking for herself to understand her first HR systems project-work. Currently she leads the Service Delivery for Phase 3 Consulting, offering an independent take on the HR systems market in the UK.
Kate’s guiding principle is that openness offers knowledge-sharing, credibility and trust, best delivered with incorrigible enthusiasm.