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. 

At Rectec we help organisations to find the best recruitment and talent acquisition technologies to suit your needs. 

From Applicant Tracking System and Recruitment CRM comparison, to vendor snapshots, and technology showcases in our unique technology marketplace, we provide fee-free tools to help you build the perfect recruitment tech stack for your business!

The post How can AI be used to promote inclusive hiring practices? appeared first on Rectec.

So how can we make sure we all take full advantage of AI to better connect with talent, whilst retaining everything about effective human-centric recruitment that works?

Before we dive into some recruiting AI nitty-gritty, it’s worthwhile pointing out that without a strategy for AI implementation, and full awareness of the limitations (and incredible breadth) of AI, you’ll have no idea of how these amazing systems can help you.

Formative AI, and our horizon of change.

A strategy and creating a list of AI priorities are very, very important. AI, especially generative AI and AI Agents are in their adolescence. New products are being released almost weekly, but one rule stands out – the quality of what you feed into AI tools correlates directly to the quality that comes out.

So before you dive into any AI platform be aware of your priorities – the more specific the better.

• Where do you see AI helping your talent outreach and recruitment? For example, are you looking for employer brand support or more niche candidate-seeking tools? 
• Are you aware of budgetary restraints and can you afford more highly-priced tools? 
• Who is going to be using AI – consultants, BD professionals, sourcers or marketers, or all of the above?
• Have you discussed AI integration with your tech vendors – is, in fact, your recruitment ATS provider sitting on exactly the tool you already need, or do you need to reach further into the recruitment technology market?

Once you have the above in order, dig into the below and start your AI journey from a place of positivity and success. 

Here is the Rectec guide on how to avoid 7 common mistakes when recruiters use AI!

When your Data = Trash.

The cardinal rule of AI (right now) is that it is as only as good as the data sets they’re trained on. 

• “ChatGPT was trained on a massive corpus of text data, around 570GB of datasets, including web pages, books, and other sources”.
• Bard was trained on “public dialogue data and web text… totalling 1.56 trillion words”.

Using the most relevant, accurate, bias-free AI tool will take some research and a bit of A/B testing, but each tool comes with limits to its referenceable data, quality of data, transparency of data and size of data set. 

Remember – AI hallucinates, so test and perfect which tool works for you!

Not testing your AI tools.

Take a target candidate base, and test your AI plugins for accuracy and quality. 

Do not, and we cannot stress this enough, simply start building new workflows, recruiting funnels or employer branding campaigns without testing AI capability.

Most importantly, you need to have a path of accountability for when things do, inevitably, need changing or go wrong. Leadership and chain of command are vitally important in factoring in changes to AI use and further investment. 

Not being transparent with your primary service user – your candidate.

Disclaimers are essential to empowering your candidate. 

If you are using AI for assessments, let your candidate know. If automated outreach emails to cold candidates are being written and sent via AI, make it clear that’s the case. Most importantly, include a clear Call to Action for candidates that they can, at any time, speak to a HUMAN!

This not only engenders trust in your candidate base that you’re working with them in good faith, but it also gives them an out when and if AI tools don’t do their job or they misfire. Good for CX, good for comms, and good for legal accountability too.

If the AI boot doesn’t fit…

Recruitment should never, ever, lose the human-centric element of empathetic connectivity that makes a person trust another with their career.

In our view, recruiters who lean on AI to replace the human will find candidates simply switch off. Innovation in the AI space is incredible. The industry is developing at a freakishly fast pace, and we’ll hold our hands up if, in a year’s time, much of the “human” is indeed replaced by NLP-based tools. 

But we stand by our word – AI is fantastic for improving SEO ranking, automating repetitive tasks, analysing data sets, building marketing plans and perfecting recruitment strategies. But it is not, yet, human. 

Use AI to augment, not replace.

Not taking accountability.

Test, test, perfect, test again. 

Never rest on your laurels. Always be looking for drop-offs in AI accuracy, or prompt responses not working any more. Recruitment is and forever will be a results-based business, and any AI brought into that fold needs to create results, whilst maintaining fairness within the recruiting process, reducing discrimination and removing bias from the equation.

This means targeted analysis of AI use, usability, relevance, and delivery of results. This means someone, anyone, taking accountability for the systems in use.

Not training your tools.

Whilst we’re still sitting on the cusp of a true AGI, a fair proportion of AI tools require learning and training to become fully effective. 

This can perhaps be better explained by prompt analysis and development of more useful dialogues in tools like ChatGPT or Bard – practice makes perfect. 

Effective AI use takes prompt strategy and iterative learning techniques. Improvements don’t happen in a vacuum, and the real strength of AI is that it can reform and rejig output based on prompt tweaks and new data, over time.

Do not silo your AI tools.

Tech stack management 101 – never silo operations, and integrate where possible.

Using AI in conjunction with other recruiting tech tools like CRMs, CMS’, Applicant Tracking Tools, and performance management systems will improve hiring outcomes and retention rates, and build a more connected tech ecosystem for your people to work and thrive.

Most importantly, AI should never supersede human judgement or act independently of human oversight, especially in recruiting-critical touch points like initial outreach, interview aftercare or salary negotiation.

The bottom line. 

We must be prepared for change, or will be drowned in innovation and miss critical opportunities to improve recruitment and make our industry as effective and useful as possible.

A good place to start is by knowing where we mostly fall down on AI understandings!

At Rectec we help organisations to find the best recruitment and talent acquisition technologies to suit your needs. 

From Applicant Tracking System and Recruitment CRM comparison, to vendor snapshots, and technology showcases in our unique technology marketplace, we provide fee-free tools to help you build the perfect recruitment tech stack for your business!

The post Recruiting with AI? Here are 7 mistakes to avoid! appeared first on Rectec.