In our latest Big Interview, we're pleased to introduce a seasoned HR professional with expertise in AI, Rewards, and EDIB
Reward and EDIB with Michael Piker
In our latest Big Interview, we’re pleased to introduce a seasoned HR professional with expertise in AI, Rewards, and EDIB. Explore the pragmatic evolution of artificial intelligence, tracing its 45-year journey from academia to second-generation AI. Delve into the practical implications of AI in rewards, addressing accuracy and trust concerns. Uncover the intersection of AI and EDIB, specifically in global mobility, and understand the nuanced changes in talent acquisition.
Tell us about yourself
I’m originally from New York City. I’ve lived and worked in nine countries and spent half of my career with big consulting houses and then half in-house. So I’m kind of a global gypsy if you will. I particularly specialise in areas like AI, Reward and EDIB.
Let’s delve into your insights on AI and the Rewards profession.
So, most people probably forget that AI has actually been around for 45 years. It was founded as a research endeavour by Dr. Geoffrey Hinton, from the University of Toronto, who eventually moved to Google Brain. The initial thrust of Chat GPT, last year, was first Gen AI, so that’s predictive analytics and machine learning.
Now we’re into what we call second-gen AI, which is Chat GPT-4, and you’ll hear these strange acronyms such as LLM, (large language models) which use vast amounts of neural networks to aggregate data and draw insights. Sounds complicated right? So, specifically to your question, AI is evolving rapidly like everywhere else, there’s vendors like Squirrel, uFlexReward, Beqom that employ Gen AI to create personalised pay, and pay predictor modelling. The key point here is they’re built around AI from the get-go, so that’s a big step change, probably the biggest disruption in reward is job levelling and job evaluation.
If you look at the transparency of setting pay scales, and setting levels in organisation hierarchy, that’s probably in the near term. The biggest area that will improve is real time reward market intelligence. From pricing the job to developing final offer value. There is a plethora of vendors that can do that now without much human intervention. Therefore, my premise here is that you’ve got to re-think how you design and deploy your reward team (OD), what you want them to focus on, and how you’re going to actually engage with AI rather than thwart it.
There’s some reticence in the reward/HR community of ‘it’s going to take my job away’. My view is it’s actually good and reward really requires disruption because it’s been doing the same thing for a long time.
Reward Professionals not currently using AI, might be concerned as to how accurate that data is, can they trust it?
This is a very timely question. There are a couple of things that are a bit strange about Gen AI. Firstly, chatbots like chat GPT-4 can and do hallucinate. Sometimes, just like the human mind. Second. I’ll be very candid. Typically, young white men in Silicon Valley who possess unique biases than perhaps the broader, diverse populace of the world are the prime coders of these chatbots.
That said, you’re going to get vague answers to specific questions that might be myopic and focused on facets of society, but not mankind at large. So, what I’m trying to say here is to use multiple chatbots. Be cognizant of the people writing the code and the algorithms… as they don’t necessarily represent society at large.
You must be a bit indifferent to the results that you are going to get, and I would highly suggest you get two or three chatbots to get an adequate answer. So let me just give you some stats. Chat GPT-4 uses 170 trillion parameters, whereas the human brain has 86 billion neurons. Meaning, you know, they can play chess and beat us, but can they do it ethically and appropriately? Be aware the Gen AI chatbots is still evolving.
It’s only a year-old in terms of the bot world and third Gen AI is going to be a big step up…. a paid step up.
What other elements should we be cognizant of with AI?
Young people can ask it to write their homework, which is a worry in the academic world. You can set parameters around particular subject matter that you want to focus on and AI will do the grunt work. Bots are increasingly commercial platforms to derive revenue. Open AI for example has a profit and nonprofit arm. Most of the big Silicon Valley tech players have their fingers in the pie. You have to understand people want to commercialise AI and make money. Google is competing against Microsoft/Open AI. Meta has its own version too. So, when you look at tools and tech, be vigilant about using them. Everybody has skin in the game to make money off it, therefore be judicious about which platform/Bot you buy, from whom you get information and query the content multiple times to get the right information.
In Reward for example. Ultimately, you still need a human intervention to level the roles that the salary grades are being applied against. Judgement matters. But AI is here and it’s coming to the UK and to the world at a rapid pace; salary transparency legislation is coming from the US/ and the EU. If you can create a bot that creates an algorithm around your whole job levelling system, it can be done now.
A large fertile area is global mobility. There are several platforms that are using chatbots to have DIY assignments.
There’s a tech platform called Squirrel that looks at scraping publicly reported salaries from job postings. With people analytics you can apply correlation analysis. So, it’s still early days and hugely exciting to disrupt the reward profession that’s been doing the same thing for too long.
AI on EDI, specifically around global mobility, is a big topic and an area that you’ve talked about recently. What’s your general overview?
Well, first thing DE&I is a fantastic example, linked to your Global Mobility strategy which can serve as role model of your DE&I strategy. If you’ve got the right people in the right role, the right time in the right place represented by gender, LGBTQIA+, multicultural and accessibility employee groups in your program then it sets a powerful example of your DE&I ambition.
Most DE&I programs have hard targets to increase representation and Global Mobility programmes amplify your focus on that. What better way than global mobility to move your talent that exemplifies your DE&I ambition. And then the link to AI like I said before, is DIY assignments, virtual assignments, golden visas, global nomads.
So, there is a lot of disruption post-COVID. There’s less volume in Global Mobility these days and those that do move for cheaper and do it virtually. So, the notion of people to jobs versus jobs to people comes into play here. You can sit on a beach in Thailand and be a golden visa remote worker without physically moving your whole family and there are AI implications to policies, programs and tech platforms through the way you move staff.
It can be systemised through a bot and decide where you want to go and how much it’s going to cost the company. You can use that to negotiate, and there are a number of global mobility platforms to do that. There’s Topia, Benivo and Equus Assignment Pro, so a lot of disruption there. Again, hugely exciting.
How is AI currently disrupting the talent acquisition space?
There are AI-powered chatbot Applicant Tracking Systems (ATS) employed in the TA space for years. Open requisitions (time to hire, time to place) analytics are powerful and then it can suggest a plethora of candidates to choose for the role using AI-instructed algorithms. AI screening has been around for a while. Take Unilever, the first step, the second step and shortlist, then through to a recruiting manager… a human.
I like eightfold platform, which analyses skills, job titles, looks at hundreds of companies for requisite skills, and focuses on skills.
What’s the take-up like? BP, Vodafone, the big FTSE have employed ATS in TA for years for selection and screening. Josh Bersin, has talked very eloquently about technology employed in the internal talent marketplace. Larger corporations like Walmart, Citigroup, Shell are very proficient in long term workforce planning.
If you have large talent volumes and you’ve got a big tech budget, you can experiment with AI led talent marketplace tech platforms. And from what I see it is expanding quite rapidly.
You don’t need to be a big FTSE to be able to experiment.
What are your predictions for the 2024 HR agenda?
So…
1) We’re going to have a vexing reality in 2024, because of Ukraine, Gaza, elections, some inflation will continue. So, navigating this adroitly, by having the right people cost parameter to get the right talent, which is probably the very top of the CPO agenda. The UK labour market in 2024 will improve for hiring no doubt compared to 2023.
2) There will be sectoral peaks and troughs. FS continues to bounce back, and FMCG is doing well. Some sectors have been bumpy, for example supply chain. So, one size does not fit all.
3) Talent If I look at the open Recs for HR roles globally is improving The CPO role which you’ve probably noticed yourself, has morphed into the head of talent role in listed companies increasingly.
There’s been this evolution I’ve observed. The senior HR marketplace is very illiquid at the moment, there are not a lot of people moving. People tend to stay in the role longer than we realise. So, if there’s more churn, I think there could be more inside-out ideas to bring to a new employer. If you read Gartner’s research, and you look at any of the big CEO’s views on CPOs, they deeply require commercial acumen and analytic aptitude, requisite depth on AI, global mindset and data acuity. And if they’ve been on assignment in another country, you know they can walk the talk by speaking another language, and living in another country, gives you tremendous credibility with your clients and customers.
Thank you to Michael for sharing his insights with us. You can find more articles like this on our Insights page
