The infinite possibilities of an AI-led future are a hot topic…but will the benefits be felt by all?
There is a lot of noise about how AI – specifically generative AI and AI agents – is already halfway towards revolutionising how we work, how we create and how we collaborate.
From coding to customer service, from marketing to sales, NLP programmes are making immediate, critical inroads into previously human-centric operations.
The possibilities beyond this explosion in generative AI (and the presumption that a working AGI is only around the corner) extend the horizon of what AI can do for more complex tasks, such as iterative problem solving and high-level reasoning.
So within this hysteria of disruption, where are the details around how AI will make workplaces better for everyone?
After all, the main benefit of integrating AI into workplace processes is to reduce the mundane, automate the repetitive, and allow humans to do what humans do best – create, reason, collaborate, ideate, laterally generate ideas, build relationships and create genuine emotional connections between people, products, services and theories.
Amidst the contradictory thought pieces and think tank panics about AI, what seems to be somewhat lost in the mania is how AI can help build more equitable, fair workplaces for many millions of people who are forgotten or incapable of integrating into analogue workplaces.
So can we create a future where AI is used for good, or are the tech naysayers right in assuming AI will only be used for illicit gains in easily manipulated industries, deep fakes, crypto-scams and hyper-capitalism?
Let’s dive into it.
Diversity, equity, and how AI can help.
According to author and Forbes contributor Tomas Chamorro-Premuzic, AI will help diversity in two ways.
- “The first is to diagnose things better, telling us what truly goes on in a culture, revealing some of the hidden dynamics underlying many of the critical interactions between people at work”.
- “The second is being able to actually measure inclusion, in particular, whether someone’s demographic status or identity can predict their actual status at work”.
The analytical power of modern AI programmes “allows us to go beyond perceptions”, giving change makers and leaders insight into “biases in behaviour”. AI fills a gap between what we think is happening, and what really is happening, or what could happen, based on evidence. AI can supplement emotionally driven HR decision making with evidently based logic, which in the case of diversity hiring, network management and fair representation can only be a good thing.
Bridging this evidence/emotion gap is the only way to build HR functionality based on real, performance-driven equity, based on real-time data. That data, and the ability to parse it, is the real power behind how AI can assist in creating a representative workforce.
Of course, this doesn’t mean AI should be used on a whim – there is ample evidence that poor AI implementation can break laws and entrench biases, so oversight is key.
It’s worth reading pieces, such as this article by Fast Company, on the pros and cons of using AI for diversity hiring practices.
Inclusivity, disability and how AI can help.
As this detailed report by Accenture titled AI for disability inclusion puts it, there are several things business leaders and AI developers both can do to help foster more inclusivity in workplaces, especially around disability access and using tech to help people work more productively.
At the very basic level it starts at the design phase. AI creators need to put “inclusive design principles in place to support “human + machine” collaboration (which is) essential to the development of fair and unbiased AI solutions”. Inclusive AI by design is the foundation of inclusive AI use.
So what does this inclusive design look like in real life? Well, it can be a poisoned chalice but again with the right leadership and strategy AI can be a blessing.
- “Biases often occur at the intersections of disability, race, gender, and other identities”, which means whatever and however AI is developed it has to be built around reducing bias between underrepresented and vulnerable groups, rather than exacerbating them.
- AI can help build more inclusive workplaces. For example AI platforms can provide better testing and pre-interview assessments, AI-based accessibility tools such as speech-to-text transcription and sign language into text systems, AI-driven employee feedback, AI-augmented accessible interview processes and AI-augmented language accessibility tools.
The tools of the future can be implemented today to help those most in need of that extra layer of support.
Minority recruitment and AI.
This piece by the Data Scientist neatly summarises how AI can help elevate minority hires in the recruitment funnel.
But much of the theory behind diversity-focused hiring strategies – such as blind screenings and automated assessments – has been known for years. It’s how they’re evolving via AI that HR pros need to be aware of.
- The real power lies in how AI improves data-driven recruitment. AI can operate between a wide array of recruiting tools such as jobs boards, social media, applicant tracking systems and recruitment CRMs seamlessly, to better communicate in real-time with specific candidates on the nature of targeted jobs, or clients on the state of play with candidate funnels and minority talent availability.
- AI can create more accurate predictions on candidate suitability and hiring success utilising data, and can better identify patterns in background, experience and assessment viability.
- Coupled with in-house NLP (like ChatGPT plugins), AI becomes more than an automated extra – they become an assistant recruiter in all but name, able to seamlessly and immediately dive into entire recruiting networks to matchmake in real-time.
With the right sort of oversight (and a fixation on making sure bias-free searches are run), AI can be the diversity hiring partner every recruiter needs.
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