William Alfred Rose. Image: Talent Select AI
William Alfred Rose, CTO at Talent Select AI, discusses bias in AI algorithms and how the tech is affecting the talent acquisition sector.
William Alfred Rose is the chief technology officer (CTO) at Talent Select AI, a company that develops an AI job interview analysis platform to assist in job candidate assessment and hiring practices.
In his role as CTO, Rose oversees product strategy and development and is a co-inventor of the company’s patent-pending AI technology.
Prior to joining Talent Select AI, Rose held various senior leadership positions at financial services company NewtekOne.
Speaking about his duties, Rose says he is “primarily tasked with finding new ways to improve the processes related to assessing job candidates, specifically with psychometric assessments”.
‘It’s hard to ignore AI’s outsized impact across almost every industry right now’
What are some of the biggest challenges you’re facing in the current IT landscape and how are you addressing them?
The biggest challenge today is the rapid pace of new AI developments and balancing that with the discipline to maintain an ethics-first approach to innovation. This is even more important in the HR and talent acquisition space, where you simply can’t ship products prematurely. For us, the process of validating the efficacy and safety of our products remains the top priority.
What are your thoughts on digital transformation in a broad sense within your industry?
For us, digital transformation requires an ecosystem-focused strategy. This applies to both our product and our internal technology demands. Just about every technology decision requires asking: what does this process need to interact or communicate with? Where are we pulling and or pushing data? How can users benefit from this feature without adding new processes or steps?
Our users are being asked to leverage technology to do more with less, but we’re simultaneously asking them to adopt even more tools. So, our aim is to find better ways to work seamlessly within existing tech stacks and processes.
‘The [talent acquisition] industry needs to drive further standards and regulations related to AI systems’
Bias in AI algorithms have become a concern for businesses in recent years. What are your thoughts on how this can be addressed in hiring?
Bias in AI should be a concern for any organisation building technology solutions, especially in the HR and talent acquisition space. The good news is there are established frameworks and testing that can be done to ensure AI systems are assessing workers fairly and equally across all subgroups. New laws and regulations, like the recent NYC Bias Audit Law, require organisations to conduct annual bias audits and make them publicly available. This is a good first step to ensure organisations and technology vendors prioritise these efforts.
What big tech trends do you believe are changing the world and your industry specifically?
It’s hard to ignore AI’s outsized impact across almost every industry right now. The same goes for the HR and talent acquisition space, where new AI tools are finding their way into nearly every process within human resources. In talent acquisition, we’re seeing the adoption of AI tools at every step, from the sourcing of new candidates to helping hiring managers make best-fit hiring decisions.
What I find most exciting is in the area of AI-powered candidate assessments, which can not only deliver more streamlined, faster assessments of candidates, but can significantly improve the hiring experience for candidates – in some cases, by removing entire steps from the hiring process. For example, if AI can analyse a job interview to produce a psychometric assessment, there’s no need to require candidates to take a separate psychometric test.
What are your thoughts on how we can address the security challenges currently facing your industry?
Beyond standard best practices to safeguard sensitive data, I think the industry needs to drive further standards and regulations related to AI systems. For the developers of AI tools, there should be a high level of transparency to both employers and candidates in how data is collected, the nature of that data and how the data is ultimately used.
Transparency will ultimately drive more accountability to ensure the industry is taking the necessary steps to safeguard the immense volume of data that is currently being collected and processed.
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