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Episode 0046 Shownotes

The European AI act & your job search

In this episode of the PostdocTransformation show, you will understand the significance of AI in the future workplace, emphasizing its role in job search, onboarding, performance measurement, and promotions, especially focusing on the newly adopted European AI Act. You will see upcoming opportunities and challenges posed by AI, stressing the need for both seasoned and new experts and leaders to upskill and reskill to remain successful in an AI-infused team. This episode is a must-listen for HR-representatives and job searchers.  

Subscribe to our weekly show on your favorite podcast platforms: Why? Postdoc scientists & PhD students / candidates will learn the basics for their career transition from research into business & industries AND will get to know a company that hires early career scientists! 

About our PostdocTransformation show

Invest in your PostdocTransformation. Welcome to the seasonal show for scientists leaping into business. In every sponsored episode, we are happy to recommend employers of choice for you. Make sure to check your readiness to leap out of science with us for free, as linked in the show notes. For your career transition, we offer customized career transition e-courses and memberships, also at graduate schools all over the world.

Maybe yours too. And if your university isn't yet our customer, enroll in your free email course for career transition made simple as linked in the show notes. I'm your host, Professor Dr. Eleonore Soei Winkels, with my team who is rooting for you. And let's build your PostdocTransformation with this episode. 

[00:01:08] Impact of the European AI Act

Source: https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence, as of 28.05.2024

Dear PostdocTransformer, we are now discussing the impact of the European AI Act on your job search, onboarding, performance measurement, and promotion in the future of work, and also of course, in the realms of HR. So this is relevant for you, if you are my bachelor, my master student, if you are a PhD. student or a scientist leaping into business, or building your own business capitalizing on AI in Europe. 

Even if you're not in Europe, but you are planning to work in a company that has a value chain or supply chain across Europe, that means it processes data or produces goods or create services in Europe. And here's my point of view: 

Every future proof employer in business will capitalize sooner or later, more or less on artificial intelligence across the value of supply chain to remain competitive. It will boost the efficiency and effectiveness in logistics, supply, buying, sales, marketing, service operations, production, research and development, management, and specifically, human resources, on all hierarchical levels, beginning now with low level office jobs, and soon, putting a rightful question mark on incapable experts and toxic leaders.

The remaining humans must be able to use, control and capitalize strategically on AI tools to remain valuable contributors and initiators for new business models. 

It's the risk and also the responsibility of the remaining humans to avoid becoming a backward looking brake with past experience, and skills. The best life insurance for your work and your career is to embrace the chance. This is a chance and also threat for season and new workers.

In short, I see huge opportunities for those of you who embrace the AI boosted workplace and to build a new or better business with AI. As past performance targets, KPIs, Key Performance Indicators, may become irrelevant for meeting future challenges, seasoned arrived workers need to unlearn old behavior and to upskill or reskill. 

New workers can embrace the change, but have to break into the job market despite having a skill set that seemingly does not fit to outdated selection criteria. If you don't work yet in business, as you are still studying or working in research, play around with AI systems within your vicinity.

This way, you get used to being monitored, and appreciate the efficiency and effectiveness boost provided by AI systems. You get better reflecting and preparing your future of work with AI. 

From my point of view and rather realistic as a former IT strategy consultant, this is an unprecedented change at the workplace and it won't go away. And that's why I had to postpone my previously recorded interviews for the PostdocTransformation Show in order to make space for two episodes on AI.

The European Artificial Intelligence Act is the world's first comprehensive legal framework on AI worldwide. As of May 24, the EU AI Act has now been formally adopted by the European Parliament, it is expected to be adopted by the council this month.

It then enters into force 20 days after publication in the EU official journal with the implementation staggered over the next two years. So until 2026, employers will have time to get ready as they will then be controlled for compliance and fined if they don't.

The EU AI Act ensures that AI systems are used safely and ethically, prohibiting certain practices that pose an unacceptable level of risk and setting out clear requirements and obligations for other AI systems and their providers, their deployers, et cetera, that have potentially harmful outcomes for the people whose data is processed.

These people are the external customers for market research, advertisement, usage data, et cetera. And they could also be the internal customers like you, if you apply for a job at that company or if you are working in that company, you are an internal customer and your work performance data is also processed and that means your performance will be measured and monitored.

And if you are promoted based on your performance or laid off because of your performance, well, then that's because you have been less competitive in a human and AI boosted team and measured by AI, most probably. 

[00:03:04] Chapter 1: Why AI is so important in Business

As a professor for Industrial and Occupational Psychology, I reserve a lot of time in my lectures to discuss with my students the future of work. If you haven't listened to my previous episodes, And you want to know the future of industries and job roles, listen to episode number four, the future of work for new PhD holders in business, but also listen to episode 22, which is about

I honestly hope that my Bachelor and Master's students in real life become the experts, and if they want to, the leaders of all our children. I'm a mom of a child in primary school and a child who enters secondary school soon. Woohoo! 

And I often say to my students, Studentsthey shall perform in a way at the workplace, so that I will want to send my own children to them so that they can later learn from them as transformational leaders. 

But regardless whether you are my student in real life. or you are a student of mine in this Postdoc Transformation Show, you will transform the people you will be working with, or even in your own business.

And you will be boldly inspiring, and find new ways of working and doing business, you will do so by creating new business models that are probably AI driven. You will find new means with AI and new venues in virtual reality and beyond so that you can solve human problems.

Machines do not pay you a salary. Machines won't pay for a solution, humans will. You will be working with humans, for humans.

Our current economy largely won't exist in a couple of years. There will be so much disruption all over the place because AI will put a lot of humans out of work. Many people do not have the capacity, the personality to learn whatever it takes to overcome obstacles and to ultimately reach the company goals.

And if you don't understand how to use AI, then the companies won't need you. AI can do a lot of jobs reliably, even perfect, without complaint, scalable and cheap. So you have to be better than AI To be a valuable contributor and to get on the payroll.

Our future will be so different to what and who has worked in the past. The past not many people will be able to participate in the future. 

AI will disrupt everything. Employers and leaders, will want to, and also have to work with AI because. Companies who do not have AI in their business processes, et cetera, won't be competitive anymore. at the end of the day, a company that holds on to the past without using AI in the future and today to prepare for that future, they will vanish from the marketplace and the remaining humans, from my point of view, will be measured and monitored by AI in the performance constantly and individually gamified to remain and become even more efficient and effective.

Definition of an AI system (OECD)

Source: https://www.oecd.org/digital/artificial-intelligence/, as of 28.05.2024      

If you are my bachelor or master student in real life, I'll be happy to discuss what an AI system is and what are the four roles. 

For example, 

1) provider

2) importer

3) distributer

4) deployer, 

both public and private in the context of our lecture on analysis and design of work for all others. I will provide a general understanding, so here's the definition. I will read out. from the OECD, that is the Organization for Economic Cooperation and Development.

An AI system is a machine based system that, for explicit or implicit objectives, infers from the input it receives how to generate outputs, AI Act categorizes AI systems as a set of tools that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.

Further, the AI Act categorizes AI Systems in four risk based categories, which are associated with obligations for the above four roles. 

1) Minimal risk. You can use that freely. 

2) Limited risk. Then you have specific transparency. So that means the companies must make it transparent that they are using an AI system of limited risk. 

3) High risk. And by the way, this is where some specialized job profiles will emerge by a Brussels ripple effect.

Let's go into the details of number three, high risk, because that affords the most stringent day to day obligations in businesses. So five examples here:

3a) certain non banned biometric identification systems, which are, excluding biometric systems, which That confirm who a person says it claims to be.

3b) certain critical infrastructure systems. C AI systems intended to be used in relation to education and vocational training. So that's essentially our home turf. AI will affect universities and vocational training heavily.

3d) AI systems intended to be used in relation to access to and enjoyment of essential private and public services. 

3e) Recruitment selection of individuals to monitor evaluation performance and behavior are considered high risk.

4) Unacceptable risk, these systems need to be phased out.

Let's go into the detail for unacceptable risk AI systems. 

4a) Social credit scoring systems. 

4b) Emotion recognition systems. Using biometric data in the workplace and education institutes exceptions will apply though. 

4c) Untargeted scraping of facial images for facial recognition. 

4d) Behavioral manipulation and circumvention of free will. That does not cover advertising, by the way. 

4e) Exploitation of vulnerabilities of persons, for example, age and disability. 

4f) Biometric categorization of natural persons to deduce or infer their race. 

4g) Political opinions, trade union membership, religious, and philosophical beliefs or sexual orientation.

4h) Certain specific predictive policing applications in public by enforcement exceptions may apply.

As you can see, almost all of these unacceptable risks already exist, and they have to be phased out, and also exceptions will apply. 

So, the AI systems that you know nowadays in your vicinity, are just the tip of the iceberg, and it will be very exciting to see in which direction this all will evolve.

But essentially for employers, there will be penalties for non-compliance, and most companies are now already auditing their AI systems landscape and how the act applies to the AI systems landscape, which obligations they can leverage to providers. And how they govern the data processed by AI systems.

There is a huge opportunity for tech consultancies and law firms. There's a huge need for AI transformation. And related job profiles for this AI Workforce Readiness Transformation will emerge. This is a huge hint for my own students. This is where the party is. And in my lecture, I will discuss differing obligations for providers, deployers of high risk AI systems. 

[00:14:39] AI in Recruitment and Performance Management

But now back to you as someone whose data is most likely to be processed during recruitment, performance management, and monitoring.

1) Recruitment. 

Just like you can use generative AI like ChatGPT for your job application. And listen also to our episode number five on how to use ChatGPT for your job application. Companies can of course support each stage of the recruitment process with AI systems. They can, for example, draft job descriptions based on generative AI.

And for my own bachelor master students, I can only stress the importance of real life work experience in other roles and functions outside of HR, because otherwise you can simply not determine the suitability, the value of the AI derived job description based on past data. You don't know what is realistic and not, if you haven't done the job yourself.

AI can also determine how to target job adverts in social media. So if you are scrolling social media based on the content that you have been looking at, you could also be targeted specific job adverts and you could as a candidate, also interact with a chat bot when you are submitting your application. And in terms of selection, screening, and also shortlisting, AI can support that. And it has the capacity to hugely reduce the time spent sifting CVs. 

And unfortunately, a career transitioner probably has a nonlinear CV, and the algorithm won't look for that. It will be streamlining and looking for the right candidates based on the algorithm it had been coded with. And so, your CV will bestreamlining. And unfortunately, most likely you won't be emerging on the shortlist because you're not having the right skill set.

Even though that could be individually legally challenged. At the end of the day, you don't want a way into the company by using a lawyer, right? So that is a waste of your time and your energy and you should find a better job elsewhere. You don't want to be demoralized in the process to find your way into a company on that route. And to be honest, as AI progresses, aptitude and personality game based assessment will score you.

And even your job interviews may now have less impact human input. I see huge opportunities for UX design and people upskilling based on AI for my own students.

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AI in Performance Management

2) Performance management. 

And that is the collection and objective, seemingly objective analysis of employee data. That means that AI is widely used as a performance management tool.

Algorithms can undertake comparisons, detect opportunities for improvement and efficiencies and generative AI could even generate a performance review. 

Here are a couple of things that we need to consider. This kind of information has the potential to make management decisions better informed and more objective. But of course, the role of regulation, such as the AI Act in Europe, is to ensure that safeguards are in place to ensure this is done ethically and fairly.

And it depends on the training data. It depends on who is training. It really depends on how applicable is that for the people who are working at that place. And once they are performing, then obviously it will be easy to categorize ready to be promoted or should be sanctioned. 

But the problem here is, you can only categorize based on indicators coded beforehand , right? So this is essentially the basis for transactional performance criteria. If that person is doing this, then it's good or bad, or even better than someone else. So we compare between a target and a current state, and that's transactional leadership. 

But the thing is, in the future of work, we need to be transformational, because we don't know how the future will evolve in this direction.

That's where we have to have transformational leadership. That is, we have to inspire, we have to motivate, we have to foster, we have to consider individually, our team members to become better leaders, experts at the workplace.

So again, where transformational leadership is required to innovate for the future, outdated and transactional performance criteria are misleading and the devil really is in the details. So how can the company ensure that the AI is not misleading?

The system looks for the right future proof performance indicators, and that's a great opportunity again for my Bachelor and Master's students of Industrial and Occupational Psychology.

It will be key to understand that Key Performance Indicators, KPIs can be deficient.

So the one who sets up the AI to look for KPIs hasn't thought of including all factors that are needed to determine good goal directed performance. And to be clear, there will be not just one way of perfect goal directed performance. Instead, there will be many ways. So how can an AI even look for KPIs for all the different variations and combinations of KPIs that are unprecedented before, because they are so novel. That's novelty detection. How can AI do that?

And then also KPIs can be contaminated. So we measure something that has nothing to do with the performance. It is sometimes even just the better machine, the hardware, the software, the data, the bandwidth, the RAM, or the disk space on your computer. And sometimes it's the better server for a given region as opposed to the headquarter, sometimes it's even the internet access differing among the countries. So you can see results and performance are really hard to measure. And just because we have seemingly better measurement means that does not free us to think strategically on what we really want to measure and why we want to react on that.

Performance measurement should also be based not on results, but rather on goal directed behavior. And for creative work, this is important. It's really interesting and related to the next point. 

[00:23:44] Monitoring and Surveillance with AI  

3) Monitoring and surveillance. 

Monitoring and surveillance are perhaps the most high profile use of AI in the workplace. And that really acknowledges the monitoring technology that has the potential to provide a safer workplace.

So for example, tracking delivery drivers use of seatbelts. I'm all for that, but also that could be overly intrusive and erode trust. If I'm monitoring keystrokes or work rate, for example, sometimes I'm just thinking and I'm not producing any keystrokes, but what does that mean? my thinking is not worth the work hours

For overt work safety, non compliance, I can see benefits. Of course I want to save people's life. But how active someone is does not indicate laziness or engagement. And when people think the great idea to achieve the goal often appears, not when it's urgently needed, maybe after some unsuccessful attempts, these overt attempts are easily detected. But the moment when your genius or your muse strikes is not easily seen and detected by AI. 

So how can AI be set up to look out for these hard to detect KPIs as well. And to be honest, I can already see see non experienced leaders or leaders non familiar with the team members who are relying too heavily or unreflectively on AI categorizations along the lines of under, low, middle, and top performer, or something like that based on the individual baseline and typical performance levels, versus how eager they to ramp up the maximum performance for urgent situations? Well, taken further as an indicator for commitment, which actually will be too short sighted when the individual life circumstances or long time worker life cycle are not considered from a POV of a leader caring for the people. 

And that is maybe a not so bright future. How do you feel about that? Maybe you also have to rewind and listen back to this episode. 

Looking into the future, on the one hand, when there is a war for talents and a shortage of skilled workers, it will be really interesting to see how eager the talents and high performers are to join a workplace where AI rules. 

But on the other hand, workers who are truly lazy will have it more difficult to work on non work related, private, or even worse, double dipping tasks with work related resources. So, receiving a salary for no work or two salaries for the same time, and that really is interesting for the companies who cannot afford to drag people with them that are not contributing anymore or never will. 

So, from my perspective as a mom, a former IT strategy consultant and as a professor who is sending graduates out to the companies, I can only say this: Companies without AI will be gone from the marketplace sooner or later. 

And if you have professional integrity as one of your values, if you are ethically a good worker, you won't be misusing work related resources for your own purposes. 

I encourage you to embrace your future of work with AI. Again, listen to the previous episode 45 as linked in the show notes, because AI is here to stay. And the EU AI Act is regulating it as of June 24.

From episode one and counting, I have proudly hosted all our Postdoc Transformation Show episodes on Podbean. As a former IT strategy consultant, I have high requirements on my tech stack and Podbean is my perfect fit for a podcast host. If you want to create your own individual podcast or want for, you know, internal upskilling and communications within a company, DM or email me podbean so I can share my experience and consult you.

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Your home work

Additionally, invest a limited time on AI side projects and then share regularly  (on LinkedIn) about the progress or your reflections on using AI tools for your project to get the attention of recruiters and decision makers who look for AI affine talents, and high performers open to work for future proof companies.

And again, make key people want you because you learned something to capitalize on AI for achieving your goals. 

And if this is the very first episode of your PostdocTransformation Show, please also listen to episode four, the future of work for new PhD holders in business. And also number 22, working out your future because they all dovetail nicely.

I really hope that all my fellow professors and lecturers regardless of their discipline are now considering the EU AI Act into their own lectures to prepare their own students for the future of work with AI.

If not, then please share this episode with your bachelor, master and PhD besties, they will thank you later. And thank you for listening.

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Have they typically earned a doctor title? Number two, For whichever company roles or units do you encourage somebody with a doctor title to apply? Number 3. How would you describe your organizational culture in which your most valuable experts and leaders thrive in? To nominate an employer of choice so that we can ask our own formative bold questions, let us know within our free email course career transition made simple.

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This PostdocTransformation show was brought to you by Prof. Dr. Eleonore Soei-Winkels

Leveraging Podcasting for Internal Communication

Eleonore:

Hey, you're still here and you are a future HR or talent management leader. Well, I want to talk to you about a powerful tool that can transform the way organizations communicate internally. How about creating a podcast like this one in today's fast paced business world? Effective communication is the cornerstone of success, so how can you engage your employees, convey your company's culture and share knowledge in a dynamic, authentic, and accessible way?

Well, to me, the answer lies in podcasting, obviously. So picture this, a podcast tailor made for your organization, where you and your real employees and leaders share and updates in a conversational, engaging format. It's like having your own radio show, but with a corporate twist, absolutely branded. 

Now, why should you consider this as a future HR and talent management professional? Well, podcasts are accessible, so your employees can tune in during their daily commute while multitasking off screen or walking, and it's flexible and it can be easily repurposed in different formats and languages.You know what I'm talking about, right? 

So, it actually humanizes your organization and podcasts allow you to bring a company's culture to life. You can interview leaders, team members, and highlight what makes your workplace unique and connect with those team members who are far away or on parental leave when they are most receptive for your internal communication.

And in the era of AI generated communications, a podcast with your business leaders in real life is a real human way to reach your employees. You can inform your people every day, everywhere, on demand, and not just during the typical onboarding and promotion seasons.

Lastly, it's a platform for continuous learning, whether it's training materials, leadership insights, or industry trends. Podcasts keep your team informed and inspired. So as you prepare to step into the world of HR, talent management and leadership, consider the impact you can make by introducing a corporate podcast.

It's a game changer for internal communications and aligns perfectly with a modern work environment. So, are you ready to inform with a human touch create a podcast with me. I'm Eleonore Soei-Winkels, the host of the PostdocTransformation Show. Do you need inspiration? Well, you can get a list of free 30 sample episode titles to be customized for your company.

Thank you for reading our full transcript of this episode. 

For season 3 & 4 of the PostdocTransformation show, we will interview industry experts, leaders in the corporate world, but also companies serving early career scientists leaping into business. 

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Because this show is for free, but we need sponsors to bring the show to you. So, please help us to help you on your PostdocTransformation.

All right, thanks for listening and I hope that you will watch our show and also listen to our show for the next episodes. And like I said, go back to the previous episodes. I think they have valuable insights for you.

Please ask away your career transition questions (connect with Eleonore on your preferred social), as we aim to create future episodes for our audience. We appreciate every one of you!

Until the next episode, 

Cheers, 

Eleonore & Team PostdocTransformation

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