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Artificial Intelligence, Data and Large Organisation’s Role in Society’s Future

Whitespace logo By Whitespace
29th October 2020

The attendees of the inaugural Technology & Innovation Executive Roundtable gathered deep in London to explore a question that, while simply put, engendered a wild diversity of talking points. "What more can be done to establish the UK as a centre for excellence for AI as a technology, and what are the economic and societal benefits that can create?"

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Key Takeaways

If there was an overarching theme to the discussion, it was around the methods and mindset needed to best harness the power and potential of AI and its cousin machine learning. Conversation in the room was – while pragmatic and even self-critical – was both enthusiastic and even empowered regarding Corporations, entrepreneurs and large organisations holding the potential resources to face and change some of the world’s big problems. As such, this round-up will focus on highlighting the potential approaches and challenges, rather than taking deep dives into the technologies that enable or demand such approaches.

How might data as a currency empower organisations, individuals and communities?

Information is increasingly an asset with meaningful value. Artificial intelligence technologies are nothing without the data they congest and interpret. If data is essentially AI’s prime consumable, then data has an increasingly quantifiable value going forward. As such, could large organisations, communities and even individuals monetise the data they generate or collate as something comparable to a currency? The vast amounts of data a body like the NHS produces has a huge value not just within the organisation, but as a commercial opportunity, and as a resource for innovation at other groups. Aggregated, anonymised data may be something that organisations, communities and individuals can sell and trade. Beyond serving as a sellable commodity, data could equally exist as a parallel to a currency, with the potential to drastically shift the balance of power with regard to what issues and agendas are prioritised within society, and with regard to the environment and beyond.

Is large industry too large to lead a data-driven future?

Large industry may be loosing the ‘data war’ to nimble, small and young companies doing very innovative things to gather and aggregate data; for example a Startup offering home DNA testing kits. Large organisation can struggle to have the agility to move with the rapid evolution of AI technology, as well as the ways in which data is provided and interpreted. Here the founding solution in the world of Corporate Innovation will likely be very helpful; open collaboration with Startups and founders; as long as those partners are fitting and needed. Open collaboration for the sake of open collaboration is rarely meaningful in its outcomes and impact.

Do you need to know how to build a car to learn to drive?

As the current generation of AI technologies have come to the fore, there has been much emphasis on trying to educate about their function and make-up. While there is certainly a need for many more suitably experienced engineers and developers in the AI space, it was suggested that too many individuals in Corporations, large organisations and other fields have been led to believe that they must understand AI and data intimately. It is arguably much more important that they are educated so as to be able to appreciate the applications and potential of data. While there is a fundamental understanding of such technologies across many – or most – organisations, the ‘understanding/appreciation’ dichotomy may be impeding adoption or potential of the technologies.

The following question can serve as a thought experiment to highlight the point: ‘do you need to understand how a car is designed and made to learn to drive one, and appreciate the benefits driving brings?’. The answer there is clearly ‘no’. As such, there needs to be a concerted effort from technologists and industry to educate workforce so as to appreciate the application and output of AI and related technologies. Who precisely will take ownership of democratising the appreciation of artificial intelligence is another question altogether.

Open-mindedness to unexpected outcomes

Artificial intelligence is often best applied with clear aims and outcomes in mind. But that does not mean one should turn a blind eye to the potential for unexpected outcomes; particularly regarding large data sets. It is not at all rare for data gathered for once purpose to reveal something else distinct, unexpected or even unrelated to the intended findings.

Furthermore, some platforms are now being founded around the notion of ‘counterintuitive data use’; for example, a loan provider that uses AI to consider an applicant’s broad interactions with the apps on their phone – and not exclusively financial ones – to deem suitability for the financial services provided. The established notion that ‘data is nothing without insight’ is particularly interesting in this context.

On a related note, a rising phenomenon is that of the general public altering their own behaviour as a result of being aware of data collection; consider the car owner driving more carefully as they are aware their insurance provider bases rates on a ‘black box’ placed inside the customer vehicle. It may be that awareness of data collation is as powerful a tool in delivering societal and cultural change as insight.

Sharing data to develop truly innovation solutions

Furthering the logic that data has the capacity to contain unexpected insights or outcomes, there may be value in sharing data sets with Corporations, large organisations and other entities outside one’s own. Some of the most impactful and meaningful solutions can come from allowing the outside world to access you own infrastructure. There is, however, an intrinsic and understandable fear that other bodies may be able to reverse engineer data to secure access to the fine details of a valuable IP. It may be, then, that all organisations would need to be open with their data to undermine any existing competitive advantage universally. Significant changes may be needed to keep such groups in step with the AI opportunity and the needs of society.

Has globalisation ‘left society behind’?

The issues of trust and transparency are never far away from conversations about AI and data. But could it be that the issue with trust goes far beyond a sense that Corporations, large organisations and technologists are ‘listening in’ on the ordinary person through technology?

In the era of aggressively polarised societies, the rise of Donald Trump, Brexit, ‘fake news’, and the Extinction Rebellion environmental movement, there appears to be increasing distrust from the masses from numerous demographics and political leanings in the ability of government, industry, Corporations, international groups and technologists to support, respect and reflect the needs of the masses. What can such groups do to regain that trust?

As global warming and an incoming environmental breakdown loom ever more pressingly, technology companies can be seen to be focusing on relatively ‘trivial’ products such as social media apps. Meanwhile, globalisation is arguably leaving behind more and more who feel isolated or deprived. Growing social unrest is hard to deny.

But perhaps the large bodies can – through regaining trust and demonstrating new or augmented priorities – move from untrusted giants to powerful problem solvers supporting wider society. Globalisation may be increasingly unpopular with the masses, but it also has the tools and resources to make grand changes with meaningful impact.

Isn’t the responsibility really governmental?

There is presently mixed feelings around the issue of government taking the lead in using technology to tackle societal, national and global challenges. That has, after all, largely been the case historically. But perhaps it is time to give more responsibility to Corporations and other large organisations? Should the likes of energy companies be given more than a voice in developing strategies for the future, and be expected to have a proactive role to play? As globalisation plays out, the emphasis of responsibility may be shifting.

Setting an example through workforce support

Collectively the human beings that make up Corporations and large organisations represent a sizable cross section of society. Significant societal benefits could be brought about through inspiring changes in behaviour from that ‘human resource’ alone, while a powerful example is also set, potentially rebuilding trust in large organisations at a wider scale. Thinking innovatively – and empowered by ‘brave and bold’ boards – companies could, for example, pay staff more to car share or work from home. Corporate values should not just be mounted on the wall in reception at head office, but used as a tool to set examples, inspire and lead beyond the walls of an organisation.

The value of time spent in the company of others’ companies

While it is a relatively simple concept, the value in spending time in other – and even rival – Corporations and large organisations may significantly bolster the abilities to be progressive, and be aware of the potential societal and cultural impact of work with AI and data. That is not to say other bodies may be doing it better; just differently. In this case, a change can be much better than a rest.

Considering ways to expose the problems

It is said that sometimes you need to drain a river to expose the rocks that may have been causing problems to passing boats. The challenges facing the global population – and the problems inherent to AI and data capture – are arguably underexposed; obscured from a clear line of site by noise, be it hype or sensationalism. As such, means must be conceived to ‘drain the river’ around AI and data.

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