The ethics of automation


Predicting precisely what’s going to happen in our world is futile – after all, data is a vast subject, one that straddles every market, industry vertical, and business globally. But there are some large and important structural trends to monitor as we enter a defining period in the data sphere that will straddle multiple industries. The biggest of these is automation.

Everywhere you look, automation is proliferating. In the data industry, as machine learning models improve and data maturity across financial services organisations increases automating processes in order to free intellectual capacity will only increase. In 2020, data automation will continue to help businesses make decisions faster, and deliver better insights to decision-makers.

But the rise of data automation creates second-order effects. Ethics is a particularly challenging area and one that demands attention from all players in the data ecosystem.


A threat to progress

The ethics of automation are complex, but the key takeaway is that we are yet to agree upon a universal ethical code for avoiding unintentional bias coming into algorithms and tainting the legitimacy of machine learning as a force for scientific progress, economic prosperity and good in our society. 

Cambridge Analytica and Facebook are just the tip of a very large iceberg. Negative headlines regarding data malpractice risk holding back adoption of new technologies and slowing the progress that’s being made across the financial services industry. The regulatory environment for data is still nascent, mainly because it is hard to regulate a global industry without barriers or boundaries.

Furthermore, a lack of clarity on precisely how data should be gathered, stored and deployed can lead to challenges in the day-to-day running of the business.  Ultimately, just because you can do something, doesn’t mean you should. As the decision-making process evolves to rely on machines and humans working together in tandem, it will become harder to promote accountability across large organisations. If practitioners can simply blame machines for suboptimal outcomes, they may be less inclined to invest time and energy in properly assessing commercial risks.


A robust ethical framework

The bottom line is that there are no clear regulations or guidelines on data ethics, and while it’s been a trending topic for some time, there has been little movement on any organisation leading the way. Sure, common sense, a healthy dose of scepticism and an intuitive sense of right and wrong are critical elements in ensuring that organisations don’t go down the wrong path with their data practices, but good intentions and self-policing simply won’t cut it as our reliance on data increases.

Here at Mudano, we believe that a robust ethical framework is essential in order for the data industry to move forward and achieve long term, sustainable growth. As a community, we have to tackle this challenge head-on, working together with local regulators to ensure that data remains a force for good. However, the challenges of applying an ethical framework are far-reaching, requiring input from Legal, Risk and other functions within an organisation. There is no ‘quick fixes’ to be had and there must be broad strokes made across whole organisational structures in order for this to have a sustained impact. We perceive the data community as owning the crucial role of facilitator in the definition and implementation of data ethics practices which is why we have developed an ethical framework within the data industry in order to be at the forefront of this movement. We look forward to sharing our plans with you in the weeks and months ahead and incorporating your feedback into our approach.


With great opportunity comes great risk

We live in exciting times. The pace at which machine learning is adopted and deployed across financial services organisations is accelerating, putting forward-thinking firms at a huge advantage over less progressive competitors. Companies that leverage data to their advantage are attractive to clients, employees and shareholders – but they are also scrutinised accordingly. 

Decision-makers are organisations are keen to exploit the opportunities posed by new technologies – but they must also navigate considerable risks, both operational and reputational. With great opportunity, comes great risk. 

Data ethics are a critical part of this picture, and should not be allowed to go under the radar. In the absence of a robust regulatory framework, organisations that proactively engage with the ethics of how data is gathered, managed and monetised can gain long term competitive advantage.

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