AI has positively impacted many areas of business and our personal lives. From software that makes the day-to-day of our jobs easier, through to intellectual tech that we can use within our homes, on the whole, AI is seen as a help rather than a hindrance. When looking at AI through the lens of D&I, many positives can be drawn. However, there are still concerns about how effective AI can be against bias.
Although AI systems have been previously used to combat bias and stay neutral, there have been many examples of AI exhibiting bias due to its programming (carried out by humans, who have unconscious bias ingrained). For example, facial recognition AI has less accuracy for underrepresented groups, and hiring and recruitment systems powered by AI have shown bias through specific algorithms, rejecting candidates due to their age, gender, race, and other protected characteristics, reinforcing discriminatory practices [source].
“Humans are biased by design. Our propensity to think fast and fill in the blanks of information by generalizing and jumping to conclusions, explains the ubiquity of biases in any area of social life.
Because no amount of unconscious bias training can make humans unbiased, it makes sense to rely on data and tech to make fairer decisions. However, AI can only be unbiased if it learns from unbiased data, which is notoriously hard to come by.
For example, for AI to effectively identify the right candidates for a job, algorithms must be fed or fuelled with past data on successful candidates. In most instances, these profiles will not only consist of high-performing individuals, but also individuals who were merely designated as “high-performing” by their managers.” - Fast Company
However, understanding these biases and recognising that they do exist within AI doesn’t mean that we should discredit AI altogether. Instead, we should use it as fuel to improve AI, harnessing it for good.
Used in the right way, AI can offer a range of benefits to businesses, from data analysis through to the speed and agility at which it can operate. An article by Fast Company highlighted that AI has the potential to revolutionise the world of D&I, but the main issue is that there is a lack of reporting, analytics, and data capture in the first place.
Only 20% of HR professionals (data taken from the HR Institute) report that their organisations establish and measure DEI analytics to a “high standard”.
If an organisation can prioritise DEI data, AI can start to have a positive impact as a by-product as the data that it’s being fed is of high quality. According to a report produced by Accenture, 98% of global executives agree that AI foundation models will play an important role in organisations’ strategies in the next 3–5 years.
“Companies must reinvent work to find a path to generative AI value. Business leaders must lead the change, starting now, in job redesign, task redesign and reskilling people. Ultimately, every role in an enterprise has the potential to be reinvented, once today’s jobs are decomposed into tasks that can be automated or assisted and reimagined for a new future of human + machine work.” - Accenture
We’ve spoken in-depth about the importance of data when using AI for DEI purposes, but business leaders must prioritise data for the best results.
Whether this is revamping your systems and cleaning your data before implementing an AI solution, or starting completely from scratch to avoid “bad” or inaccurate data, having the attitude that you only want the best quality data for your AI-powered DEI solutions will generate better results, as well as ensure that you start things off on the right precedent.
AI has the potential to make us lazy - and putting all of your metaphorical eggs in the AI basket isn’t the best way to go when using AI for DEI purposes, particularly if this is a new concept within your organisation.
Much like ChatGPT can aid faster and better writing, you wouldn’t assume that all writing professionals would use ChatGPT as a replacement for their own brain. The same can be said for AI in the context of DEI. Think of it as an add-on, a helping hand, a benefit. If you start to rely on AI as a sole solution for something as sensitive (and human) as DEI, then you can enter a slippery slope of bias and inauthenticity.
“Focus on people as much as on technology, ramping up talent investments to address both creating AI and using AI. This means developing technical competencies like AI engineering and enterprise architecture and training people across the organization to work effectively with AI-infused processes.” - Accenture