Artificial intelligence is your new assistant

Hello AI,

It’s nice to meet you.

Why are people filled with fear when they hear Artificial Intelligence (or rather Machine Learning) is being deployed?

For the most part, employees fear automation will take away their jobs, and they are partly right. Certainly, the more repetitive elements of daily activities are likely to be automated, provided they are simple enough tasks that can be packaged neatly into an algorithm.

So then, why doesn’t that make people more hopeful about the future? They should, if relieved of boring tasks, be able to progress to more interesting roles within their organisation. Find personal fulfilment in performing more creative tasks, which require their unique human capabilities, for instance, imagination.

However, this is not always the case. Technological change has happened very fast in many organisations, driven by a renewed urgency to reduce costs and increase efficiency still further. But, efficiency is not everything. And many organisations have failed to account sufficiently for the human factor in the transition.

If human capabilities and more importantly future potential is not being mapped against new technology and processes, it is going to lead to resentment, resistance or even a complete failure in the adoption rate of tools powered by Artificial Intelligence or Machine Learning, which the company aspires to achieve.

It is therefore not surprising that the failure rate is known to be relatively high. Different statistics ranging from 70-90% indicate businesses have not fully realised their potential; let alone reached maturity in their digital transformation. It is simply not a means to an end. Rather it needs to be an ongoing process.

Moreover, despite their best efforts engineers are frequently disappointed to see their perfectly efficient systems, are not readily adopted by the workforce. Add to this a general lack of preparedness and deeper understanding about the significance of Artificial Intelligence, both in terms of what it can do and more importantly, what it cannot do.

In terms of significance, we should be focusing our attention on fundamental business ethics and human values, since Artificial Intelligence and Machine Learning systems rely heavily on data. We need to start by asking the basic questions:

• Which data are we collecting and why?
• Who has access, what do they see or need to see and why?
• Most of all, how can we guarantee to all our stakeholders, that all our business practices are conducted in the most ethical manner possible?

Artificial Intelligence is about to take a great leap forward. The more widespread the deployment of Machine Learning becomes, since data is now readily available, the more advanced developments are occurring at an increasingly fast rate. And the use cases are not always scrutinised as thoroughly as they might be, for instance, for the potential to cause harm whether unintended or not.

This has resulted in a cascade of high profile resignations from leading technology companies, over highly sensitive issues and reputational damage has followed.

Consequently, we now have a publicly available register of “incidents,” whereby the larger technology giants are beginning to own up to their mistakes. Whether or not some of the inherent product risks will be successfully mitigated through open source development remains to be seen.

In the absence of comprehensive legal and regulatory frameworks to guide companies (a pioneering legislative framework was only recently published by the European Union on 21 May 2021), the Boards of Directors have improvised and issued their own policy directives to govern new technologies.

But shouldn’t this all be a matter of common sense? Provided there is a strong moral compass and it is being upheld by the decision makers, at the very least we can attribute equal importance to human values as we do to market values. We should therefore be making the “right” decisions with or without the complete legislative or regulatory framework for guidance.

Technology is moving very fast, legislation and regulation less so, partly because there are areas, which require time to assess both the economic impact and the potential societal impact of rapidly occurring technological changes; and partly because they are slower moving disciplines.

Complexity, meaning we also need to pay attention to the detail, not just the general or the general law of averages. When reviewing strategy for instance, the guiding principles or ethical values of the enterprise, it need not be complicated further.

If, for instance we choose to apply common sense (an exquisitely human capability as yet not be replicable by the computational systems currently being deployed), as opposed to focusing attention just on the commercial value.

Digital Transformation is a journey, not a destination, with different rhythms and tempos; and it most certainly requires human ingenuity to yield optimal results. Transformation means transitioning from one form or state to another. This also means that both the business model and the process of operationalizing the strategy to support it are constantly evolving.

Whilst you are seeking to improve the consistency and quality of your outcomes through Machine Learning, you may also unwittingly create new possibilities for harm. Hence, this technology needs to be scrutinised continuously, not just during the production process, but also ongoing once it is fully operationalized; and it does require a “human-in-the-loop.”

The guiding principles for Artificial Intelligence Ethics can be described as follows:

• Transparency
• Explainability
• Auditability
• Interpretability
• Fairness

The production process should be transparent, particularly with regards to the source and use of the data, making data anonymous wherever possible and appropriate to do so.

It should be possible to explain how the “system” operates and how it derives certain outcomes or outputs. But, that does not mean to say we, the human beings, should take the output as an oracle of truth. Rather we should use our creative thinking and critical thinking abilities to interpret the results in the “right” way and/or question their suitability.

For the Artificial Intelligence or Machine Learning systems to be audit worthy, the appropriate documentation will need be kept and rendered accessible to a non-technical person for assessment purposes.

And finally, fairness, a fundamental human value should be embedded into the systems being used right from the start of the design process, before even attempting production or fully operationalizing the chosen systems.

Whilst we may not be able to fully eliminate bias, at least with a “human-in-the-loop” by design, we have opportunities to take corrective actions throughout the process and operate those “checks” and “balances” iteratively going forward on a continuous basis.

If used responsibly, Artificial Intelligence when coupled with human ingenuity will enable the enterprise to create the conditions for transformative economic value. By up-skilling the workforce and nurturing creativity to foster innovation-led growth, which can make a real difference to people’s lives.

This technology can help to turn uncertainty into a better understanding of the situation emerging before us. We can leverage data from past events to gain further insights and better assess intrinsic risks. This will help us to respond faster and adapt to changes in the markets and consumer demand, also making good use of advanced analytics.

However, for the benefits to come to fruition, it will be necessary to undertake radical structural and systemic changes to render the enterprise future-fit, meaning, fit for its future purpose.

It will also mean changing the ways of working by design, and this is where the human factor plays a critical role. To impose such changes without first working on building consensus and building a more open culture is in fact a short cut to failure.

To successfully execute your digital transformation, it will be far better to seek effectiveness over efficiency in processes, technology and the use of data, particularly in the earlier stages of the process. Communication is of course a critical factor to success and if anything it should be overdone to ensure everyone is up to speed and fully understands the process as it develops.

There also needs to be a full-time conductor of the orchestra with sufficient authority to bring back decisions to the core business strategy, as often as needed, if events should start to dictate a far away deviation from the desired goals.

Efficiency will then be the longer-term gain approaching maturity, provided that iterative processes are effective and the learning is systematically embedded into the core business strategy. It is often a question of less haste more speed.

If digital transformation is correctly executed, not only will you have a happier, healthier more creative workforce, better able to perform their duties; but you will also have in-built the adaptive resilience and new business capabilities to drive the enterprise forward.

Your value creation efforts will be much more successful and new sources of value may emerge continuously as the process evolves. The added benefits will include cost-effectiveness, less waste, better management of resources, including raw materials and ultimately lower carbon emissions.

Artificial Intelligence and Machine Learning Systems can certainly assist you in developing a new competitive advantage, by crunching the large amounts of available data much faster that any human being could do; particularly with the advent of quantum computing which is set to become more mainstream in a shorter timescale than previously anticipated.

However, with enhanced human intelligence, great ideas will not be in short supply and that will provide your true competitive advantage. Since talent is the more scarce resource coupled with great ideas and the “know-how” to develop and execute those ideas successfully, it would be wise to build these considerations into the digital transformation process itself.

Moreover, human intelligence enhanced by advanced Artificial Intelligence and Machine Learning tools will create a new competitive advantage in real time. You will also foster the ability to create an enduring legacy for future generations, which has to be the ultimate prize.