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Positive & Negative Effects of Artificial Intelligence

Recently, AI-powered facial recognition technology that was being used for security and law enforcement was shown to be biased against, well, pretty much everyone other than white males. This news came as a shock to the public and saw the technology banned in cities such as San Francisco.

However, it’s an issue I have noticed behind the scenes for a while. But artificial intelligence as technology isn’t morally good or bad – it just is.

It’s useful to think of AI as being like a toddler. It can learn, develop and improve its capabilities over time, but it isn’t smart enough and doesn’t have the emotional intelligence to know the context and impact of its decisions. If we utilize AI with care we can improve these outcomes, including those related to diversity and inclusion. However, if AI is used carelessly, this can undermine its benefits and limit success for our people and the organization as a whole.

Employers can leverage the power of AI in their hiring, employee development and engagement processes.

Negative effects of AI

Your mind may jump to something you’ve seen in a science fiction movie when you think about the negative impacts of AI – but the AI I’m talking about today is less overt in nature.

Artificial intelligence algorithms can be found in processes in everything from child welfare to recidivism rates. If incorrect data is included or if the algorithm includes an underlying bias, the results could be disastrous.

For the workplace, these negative impacts can be seen in recruiting decisions which see employers avoiding hiring qualified women and minorities. This saw Amazon come forward last fall and share its own challenges with these processes, which saw some disparage the company for its results. However, I believe that sharing this cautionary tale was courageous, particularly if it helps other firms realize the challenges that may exist.

Positive effects of AI

Simultaneously – the opportunities AI presents cannot be ignored. I recently spoke with IBM’s Distinguished Engineer Liza Seacat Deluca in a podcast interview where she explained that the best way to create unbiased algorithms is to have a diverse team creating the software. This helps the team think about outcomes for a variety of individuals, not just a homogenous group.

There are some great examples of how AI has helped in the workplace:

  • Uber has cut the gender pay gap in half compared to the rest of its industry, using an algorithm to set pay rates and schedule shifts for drivers. This has improved pay equity for its 2 million drivers internationally.

  • Unilever has moved from an exclusively human-driven approach to recruitment by using automated assessments and asynchronous video interviews, and this has helped it bring talented, diverse graduates into the organization.

  • I coached a startup in the HR Technology Conference ‘Next Great HR Tech Company’ competition who used a chatbot to analyse employee feedback surveys and performance review data. This helped develop managers into better leaders by coaching them on their individual performance issues. Developing all leaders from a variety of backgrounds would see a greater level of representation in the C-suite.

An unbiased approach can lead to better outcomes for diversity and a range of other factors. This is because, while machines are really great at certain things, they are terrible at others. That is where humans need to come in.

The core human skills of work

If we look back, we can see that every time automation has been introduced, the resulting jobs are more human than the ones that preceded them. The more ‘robotic’ components of the job are automated, which leaves it fundamentally changed. This means that jobs will shift into more human components and soft skills will be highly valued by employers. From my research, I have identified a core set of skills to prioritize to avoid being tackled from behind by this algorithmic era.

These skills are compassion, collaboration, creativity, critical, thinking and curiosity. It is essential that we look for ways to develop these skills in ourselves and in our organizations.

These core human skills will set us apart from AI, algorithms and bots for the foreseeable future.

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