AI: More human than we think

Current discussions about AI veer wildly. From dystopian predictions of a robot takeover to more halcyon scenarios where machines become our servants. The reality is far less binary and more blended. Complex, multidimensional and multidisciplinary —AI is more human than we think.

Once thought of as limited to sectors deemed ‘ripe’ for disruptive technologies—AI and automation are rapidly moving into new domains like HR and Learning. 

Gary Kildare, Chief HR Officer, IBM Europe, believes the workplace is ready for this change.

Moreover, he says, “it's not just a phenomenon or a fashion trend of our time. A shift is occurring in both our organisations and the world at large. If you look at the way we are starting to behave and to operate, then we're using technology in ways we probably didn't even think of five years ago.”

The future is augmented

The term artificial isn’t one Gary subscribes to. He prefers augmented. 

He strongly believes “the notion of harnessing human and machine together is so much more powerful than the whole notion that humans aren’t going to be necessary. Organisations have deep skills, deep capability, deep data and deep analytics. By harnessing these capabilities alongside working with human effort, you really get the best of both worlds.”

Experimentation is the path to implementation

Businesses are battling disruption from a variety of spaces—some known, some unknown. While simultaneously under pressure to remain cutting edge. The truth of the matter is, the technology is still very new and immature. 

Yet unhelpfully “you see newspaper headlines criticising a particular technology because it's not doing exactly what everyone thinks it should.” Organisations need to approach it as a learning process argues Gary. And, accept there are no quick solutions. 

He goes on to suggest business leaders “need to be experimenting because this is how technology starts. You adapt it, you modify it, and eventually, you begin to see progress in the right way. If you're not experimenting, then what are you doing? 

Furthermore, new ideas don’t emerge from the ether. Successful experimentation requires collaboration “across organisations, across different disciplines, beyond the organisation and into the broader ecosystem,” says Gary. 

Tackling the skills gap with multiple stakeholders partnerships

In the age of AI, the demand for new, yet unknown skills will grow exponentially. How can businesses keep up? 

Gary explains that “each of us will have an obligation to continue to learn and grow.”  

But he warns the current “learning and education model is bankrupt.” 

Instead, a stakeholder approach is needed alongside more investment. “Organizations have a commitment to their people. They need to invest if they want the best skills. But other professions have a part to play like universities, the government because if training is required for your whole life, we need to be geared-up to support it.”

Access should not be a privilege of the few

Digital inclusion is not solely the responsibility of employers, but society as a whole. 

Gary gives a stark warning about the global impact of the lack of access and digital exclusion. He argues that it is “essential we don't create a world of winners and losers because some people have access to technology and others do not.” 

His view is that the future lies in young people. “We have to make sure that young people in particular are being encouraged into these roles so they gain the skills needed for higher levels of pay and can support the broader advancement of society as a whole.”

The ethics of data will become even more important 

“It's not the case anymore that the workplace is the only place where employees use technology,” observes Gary. 

From gamification to interactive technologies, algorithm-driven analytics provide tremendous insights into who we are. But, who controls this data?

At IBM, explains Gary, “the data is owned by our clients. We are also willing to share the algorithms we use to make sure complete transparency. But there are situations where you may be a client or a customer, and you don't know who owns the data, or you may think you do, but actually you don't. And so that transparency element is missing and that’s a worry.”

Final thoughts 

It’s clear AI brings a range of new challenges to the table from skills gaps, implementation failures and uneven access. A commitment to stakeholder collaboration, experimentation and life-long learning is needed if we are to resolve these problematic questions. 

Organisations need to tap into their own rhythms to identify solutions that reflect their strategic goals and the needs of their employees. A one-size-fits-all model belongs in the past. As technology continues to disrupt traditional ways of working, a new paradigm is emerging where augmentation fuses machine and human to push the boundaries of both the workplace and society in the 21st-century. 

This article accompanies a recent interview with Gary Kildare as part of Headspring’s Learning REWIRED podcast series.

To listen to the full episode with Gary, and interviews with other leading thinkers in organisational and individual transformation, click here.

 

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