Not-so-impartial AI
The House of Lords’s recently formed AI committee shared a short “AI Code” to try and influence the development of the AI industry, rather than “passively accept its consequences”.
It touches on things like the concentration of data with larger companies, the need for more competition in the industry, and the necessity to educate the public about it. Mostly, it focuses on the ethics of AI, an ambitious undertaking if there ever was one.
Two principles of that code are particularly interesting for recruiters. The first one get back to the timely subject of GDPR and data protection: “Artificial intelligence should not be used to diminish the data rights or privacy of individuals, families or communities”.
Data privacy was already at the center of the public eye because of the GDPR coming into effect, of course, but it’s now an ultra-sensitive subject, partly due to all the great press that Facebook and Cambridge Analytica have been getting in the last couple of years, and the global conversation they have sparked. We’ve touched on the ethics of using candidate data before, so we won’t talk more about this principle.
We’d much rather discuss this one instead: “Artificial intelligence should operate on principles of intelligibility and fairness”. It’s a lot trickier because the issues surrounding artificial intelligence and fairness are not always obvious to buyers of AI-powered software.
AI for recruiting: what is it?
In terms of decisions with potentially catastrophic consequences on people’s lives, recruiting is pretty high on the list.
We use AI-powered technology in many aspects of recruiting work:
- Ideal does initial screening and scoring based on resumes and augmented data
- X.ai schedules meetings using a bot
- Filtered.ai generates interview tests for engineers
The definition by Vishal Maini from DeepMind, is one of the most complete out there, and his Machine Learning for Humans is a good place to get a semi-technical intro to the subject.
A bunch of other companies – including Beamery – use AI or machine learning in some form or another to accomplish parts of the recruiting process.
And they should. There is a lot of room to become more efficient as humans by giving the repeated, process-heavy work to machines. That time can then be used on tasks where human judgement or contact is necessary, like meeting with candidates face-to-face or assessing their relational skills.
