In our latest Human & AI Podcast, we had a conversation with Robert Neuhauser, Siemens’ Global Head of Talent and Leadership, touching upon a broad range of topics at the crossroads of Human (Resources) and AI (Technology). In this article, we would like to share some highlights from our exchange as some food for thought. Please chip in on our conversation by using the comment function.
Technology with purpose – the race between human and technological development
If we look at digitalization in general, we see many advances in technology and business models. Everything seems to scale and move at a tremendous speed. In large organizations it gets super tricky to reflect on the actual impact of one’s very own work. Do you think that we are currently setting the right priorities, when it comes to staying human over the technical advances? Or are we just blinded and fascinated by the advancements that digital technologies provide?
I think this is an extremely important question that you’re raising. And I think both – human and technological development – need to move forward at same speed. And this is a challenge. And therefore, at Siemens, one of our strategic priorities is indeed “technology with purpose.” We very deliberately phrase it this way because if technology starts to decouple from how fast people understand what the purpose of this technology is, it is not sustainable. You need to develop the understanding for the purpose and the understanding for the technology at the same speed. If people don’t get it anymore, not only from a pure skills perspective, we lose the people that could use the technology, and we lose their acceptance.
Companies with a purpose – is it a fact or a fad?
Siemens has quite early committed to what’s called “being purpose driven.” But if you look at the media and what other companies are doing, one sometimes gets the impression that there seems to be a bit of whitewashing or “purpose-washing” going on in different industries. I think it’s nevertheless a very important discussion. There is a lot of data indicating that employees desire to work for organizations whose values align with their own. And that means there is a bigger impact beyond stakeholder value sharing, the financial aspects. It is about the role a company plays in creating social, responsible and sustainable ecosystems. Do you feel that we are moving from the traditional product-market fit to a product-planet fit?
This is a nice slogan and I believe this is indeed the case. I’m convinced that many of the challenges that lie ahead of us, as a global society, can be solved with technology. And our early talents, who are a good indicator for change, are asking us to be a company that that provides technology, not only for the technology’s sake or for the financial gain, but for solving those problems. And honestly, this is one of the biggest assets that we, as Siemens, can offer to digital talents. We can tell them: Look, this is about helping to make manufacturing more efficient and save resources. This is helping to transport things in a more simplified way. This is helping to use equipment more effectively. They can translate it into what this means for society and it helps us to attract them. They get bored by working on the next version of how to extract money out of people or offering them new, cooler advertisements. Instead, they want to be contributing to something that matters.
AI & Leadership
Let’s talk a bit about leadership in the age of AI. Is leadership a different thing in the age of data analytics and data-driven organizations, or do you say the same paradigm holds still?
In essence, leadership is a lot also about making sense and inspiring people. And it has been like that for decades. If I look at today’s environment, AI takes over parts of the making sense aspect, but still leaves us to solve the final problem ourselves. It only prepares data and decisions, at least for now. AI has specific aspects when it comes to ethics and things like that, and we need to be careful when letting it take over the making sense part. So, if leadership is about making sense and inspiring people, I would not say that the fundamentals of leadership have changed. I guess what is currently impacting leadership most is that our environment is getting less and less predictable.
Inspiring innovations – in HR and beyond
If you look inside or outside the Siemens cosmos, are there any innovations or advances in the field of artificial intelligence that have really inspired you?
Probably a rather boring innovation at first glance, but what really amazes me is the progress in speech recognition, translation services and text creation systems. I guess we haven’t yet fully understood how this could also impact society, if we can talk to each other without any language barriers across countries. I guess this will change more than we think. And it impressed me from a technological perspective what amazing progress we have made over the last couple of years.
Yes, I agree that is amazing. It accelerates accessibility, not only to technology, but also to become active in general. If I observe my daughters, how they interact with whomever and whatever, whether it’s on Twitter, TikTok or anything else. They are so naturally connected and technology helps them translate automatically, so this connection is very seamless. It’s amazing.
AI in HR – What’s the current status?
Also, there are many advances in personalization/individualization technology that we see in social media or other applications. This technology can also be incorporated in the HR realm, like in identifying or ranking talents, predicting salaries, or improving employee health. There is a lot in development out there. What’s your view on implementing AI and machine learning technology in HR?
One of the key fields where currently lots of venture capital is flowing into is the HR space. So, there is a lot of innovation going on. Last year we ran a very extensive benchmarking and market analysis project where we screened about 130 to 150 solutions in the HR space. We wanted to get a feel for where solutions are mature enough for actual deployment and where it’s only the fancy marketing buzz but nothing behind it. The result was that about 50 percent of the AI solutions were within talent acquisition and then there was a second cluster centered around employee health. In these two areas we saw most of the solutions close to deployment or really in use, many other use cases were only in the marketing phase. Don’t get fooled by overly positive marketing. Many of those things are still in the very early phase and not on the level to fulfill all the legal requirements that sometimes come with application in the global landscape. But we see enormous innovation speed, so you have to update yourself every few months.
You can automate quite a lot of your processes and not only automate them, but even make them better by personalizing them. But be really careful about the legal constraints.
…and what about ethics?
During the pandemic, it has been rated that one out of four companies has purchased new technology around AI to track and monitor employees. That doesn’t sound like putting more trust and empowerment in the folks out there. What’s your view on this?
I start with the standard answer I give, whenever technology is questioned: Technology in and of itself isn’t good or bad, it’s how you use it. For example, if you track people, as you just mentioned, if you do mood checks and things like that, this can help you support your employees in improving their mental health. So, this is the good news. The bad news would be if you decide to get rid of all the people with a bad mood. Same technology, completely different use cases. What we need to learn is to be very observant of those technologies as they evolve, but at the same time actively drive the discussion of what we want to apply in our company as the ethical boundary conditions. What do we want? And this is independent of legal requirements. This will also be a differentiating factor between companies, as it is shaping company culture. What do you allow? What not? We will have to have these conversations a lot more in the future, and make sure to have the right stakeholders participate and to be fast enough. We have to be at the same pace as the technology moves forward. Highly dynamic discussions on the ethics and what we want to use.
.. and the role of bias?
That’s the aspect of having guidelines in place before you actually need them, so people can orient upfront and you always know where the boundaries are. But, Robert, when we talk about HR and AI, we should probably also talk a little bit about the issue of bias. There are over 180 different types of human bias defined by psychologists. And each one of them can influence us in the decision-making process. But it seems that in AI we mostly talk about challenges of incomplete data. Would you say a potential intelligence system could have the same number of biases? How do you expect those biases to influence the development of artificial intelligence?
Absolutely important point. We need to be very careful with the speed of our adoption. In HR this is really one of the big challenges. The question is: Could AI be the better, non-biased human in a sense? And the answer is currently “no,” because at the moment, AI learns from biased behavior and thought, even though we put a lot of effort into creating unbiased data sets.
The algorithms themselves are not the problem, they are maybe 10% of the problem, 20% of the problem is “Do we get enough data?” And the remaining 70% is “How can we guarantee that our AI is trained with unbiased data?”
A second and even more important challenge is the legal aspect, when you make decisions based on AI. Especially when, due to a bias in your system, you systematically create disadvantage for, e.g. a minority or ethnic group. There is a big difference, if you make a mistake as an individual in a company, or if that mistake is built into your system, causing systematic disadvantage. It is a huge problem we need to work on very hard and to find the spots where we can really trust in AI and where it is better than the human and can help us.
It’s super tricky. I’ve been in innovation for a while and it seems to be like a never-ending journey.
A never-ending journey indeed – and we are travelling together. Applying AI technology in meaningful ways for the benefit of our employees and customers requires us to be in constant conversation.
What do you think about using AI, for example, to improve employee experience at Siemens?
If you are curious about our full conversation, you can enjoy it here: