Ep 4 | Decoding Future Leadership | Capability and Bias
EPISODE 4: Capability and Bias
We now live in a world where talent is rarer than capital. Decoding Future Leadership is an audio-visual podcast breaking open the capabilities, technologies, growth strategies and mental fitness required to lead our future working world. This week, Dr Marcele Di Sanctis, Managing Partner of Fisher Leadership, interviews Professor Bob Wood, Director at the Futures Academy, the University of Technology in Sydney.
In this episode of Decoding Future Leadership, we discuss how to deal with bias in a world where technology is a powerful tool to increase accessibility and inclusion or an invisible system coding bias into every opportunity. How can we best tackle this risk head on to ensure we take an ethical approach to talent and bring our companies the competitive advantage diversity offers?
Our guest today is Bob Wood, a Distinguished Professor at the University of Technology Sydney, Honorary Professor at the Florey Institute, and Founder and Director of Research at the Centre for Ethical Leadership, Ormond College, University of Melbourne. His research into bias, adaptivity and the implications of technology when it comes to talent acquisition and capability development have been seminal. Bob is interviewed by Dr Marcele De Sanctis, co-founder of the Centre for Leadership Advantage (CLA), a team of organisational psychologists, scientist-practitioners, leadership specialists and thought leaders who design evidence-based, research-supported solutions for global, ASX-listed, large private and public sector clients. In 2020, CLA was awarded an exclusive position on the Financial Review – Australia’s Fast Starters 2020 rankings, and in 2021, CLA joined forces with Fisher Leadership.
Professor Bob Wood begins by reminding us that any measure is simply a data point, not a fact. When it comes to technology and assessments of capability, he stresses the importance of testing how data have been validated. Many technologies in the market have not been validated, and so we must be very intentional about how that data is being used. This, Bob says, is a weighty responsibility for HR decision-makers, because as we know, data by its very nature is being used to discriminate.
Bob makes the point that what we term ‘bias’ and ‘expertise’ are both simply knowledge stored in long term memory.
The models we build-up may be a very useful form of expertise, but the inputs may be inappropriate for certain groups of people, and certain working conditions.
Marcele explores the conundrum of global multinational organisations whereby a central HR team must decide and define what ‘high potential’ looks like across many geographies and discreet sets of cultural environments. She stresses that when it comes to selection, the profiles we create are based only on what we know. How many people are not being captured as potential candidates, simply because their capability shows up in a different way? We create a profile based on our definition. How do we create aspirations for the talent we don’t know how to define, but know we need? Marcele notes that many organisations say, “Oh we want diverse talent, but we just can’t find anyone.”
As leaders, we all have a role to play in challenging what high potential looks like, and to cascade a globally localised approach across the geographies. This is no small feat. How do we define ‘high potential’ in a way that allows for difference? How do we recognise cultural nuances comprehensively? What is the alternative to going global with guidelines on talent?
Bob explains that data points are also very much bound to a point in time. We constantly need to update our measurement outputs, and ensure we are implementing a dynamic process, as a fixed process will inevitably fail. Bob notes that the search for certainty can override the search for accuracy, particularly when there is complexity in the data. For example, when data gives us extreme differentials, we can use them wisely, but small differences in data points are too often over-interpreted.
What is our best defence against bias in HR technology and predictive systems? Being alert and non-defensive to the possibility of bias. Bob says it is all about the teams at the heart of the implementation, are they constantly challenging how is the decision-making process is creating space for a robust challenge? Without constant rigour, bias too easily becomes institutionalised.
As the conversation wraps up, Marcele questions Bob on the new capabilities emerging in dynamic competency frameworks today. Bob discusses how leaders must be cognizant of the new requirements around intentional communication, hybrid facilitation, and psychological safety.
He discusses how online meetings can leave us wanting when it comes to the cues needed to pre-empt psychological safety. In-person contact allows all our human senses to feed into how we are making another person feel; how open to the conversation they are. Online, we are trying to read everything through a flat, two-dimensional window. Leaders of the new world will be those that understand and are capable of facilitating inclusivity and vulnerability in hybrid meetings. They will understand that almost every moment of communication is now an intentionally created moment.
Today, technology carries our language, and language carries culture.
The PeopleStrong Talent Operating System is an AI-powered integrated talent management platform that helps organisations recruit, mentor, retain, and engage their future-ready workforce. It takes disparate and distributed data points illustrating the lifecycle of an individual and offers insights for career decisions moving forward.
Decoding Future Leadership is a collaboration between PeopleStrong, APAC’s Customer’s Choice for HR Tech, and Fisher Leadership. Each episode addresses the challenges of a hybrid workforce, with a blend of human capability and HR technology solutions. Reach out to learn more: firstname.lastname@example.org