Why talent professionals and data scientists need to build a framework for AI applications…
Over recent weeks I've heard a lot about how talent professionals are being challenged by the opportunity that AI brings to the hiring process.
The competitive advantage that AI is already bringing is undeniable. It mostly lies in the speed with which data analytics will screen written as well as video applications. This and the accuracy that automation delivers. Both are powerful tools for a busy talent acquisition team working hard to attract the best talent in the context of a candidate-driven marketplace.
The drawbacks are the natural hesitation that we humans feel about being written out of some of the process, plus the general mistrust of bias that may be built into algorithmic systems. AI tools can expect some pushback from the professional talent community this year, especially around possible bias and the need for external validation, as reported widely - What to Expect top 2019 HR HR Tech Trends.
Here's the rub: the broader opportunity with AI lies not only with the technical innovation, but also the social evolution that our working relationships are undergoing.
We are being challenged by the pace of change that technology is bringing to the workplace. The bigger challenge might just be the way that our business relationships are changing so rapidly. How we connect and engage with clients, stakeholders, customers and employees looks so different now to only a couple of years ago, doesn't it?
We need to find the answers to the bigger social question that automation raises around the future of work. How do we navigate the social impact that AI will bring? How do we secure our future relevance in the workplace?
How we look at our roles in the workplace and our careers has to evolve. If rapid change through innovation is the new normal, then we can no longer think of a job as a single employee-employer relationship. It is something much more fluid, defined by our social and technical skills and the tasks we can perform rather than by our location, job-title, or employer. We might, for example, have skills that bring high value to more than one department or revenue stream.
When we consider that the needs of a company continually change (through technological innovation) and our skills will not always match their needs, then we start to recognise the need to ensure that we continue to be valid in the workplace, by being open to learning new skills.
Lifelong Learning will be the new norm, and employers are trying to catch up because employees are already investing heavily in this process.
AI is certainly one of the drivers pushing the boundaries of the nature of our working relationships, our working styles and how quickly we need to adapt. In turn, this changes the skills that candidates recognise as important to be relevant in the employment marketplace. The fact that we commit to taking these new social and technical skills on board means that AI is mitigating some of the pain experienced in talent attraction.
Most importantly, we as technology builders, need to be more proactive in advocating social change to go hand-in-hand with technological change. If we don’t we may pay a high price. Opportunistic politicians that now blame immigration, renewable energy, or global warming for stagnating wages may turn AI into the next bogeyman. If we, as a community, don’t ensure everyone feels the benefits of the AI revolution, we might find ourselves a target, and justly so.
If you agree that we all need to drive innovation responsibly, then let's start to frame what we want that to look like. Let's build AI solutions that meet this wider social change.
The obvious starting point is creating a community where data scientists and talent professionals can find the answers to the right questions in a collaborative environment.
Paul Kitchen is Director at Toucan Digital and a proven commercial partnership strategist helping SMEs and startups to build sustainable commercial relationships.
Passionate about delivering best of breed solutions to clients like Swyg and then working collaboratively to help realize their objectives and achieve sustainable growth.
Paul is a guest blogger for DANGERFIELD.