The CFOs versus the machine: futurist Graeme Codrington gets into it

Many CFOs worry that machines and robots may affect their jobs in the near future. Futurist Graeme Codrington, strategy consultant at TomorrowToday Global, believes they’re right to have this concern. Thus, CFOs need to partner with machines to make the most of the new world of work – and become more human to keep adding value, he says.

The last 200 years have shown us clearly that new technologies both improve the world and destroy – or at least transform – jobs. Right now, it’s computers, smart devices, the internet, social media, and algorithms that are revolutionising how we live, and transforming – and destroying – jobs at an alarming rate. As a CFO or management professional, it’s easy to think that this new digital era is likely to affect the jobs of lesser skilled workers and staff members, rather than yourself. But actually, the next wave of job losses is going to be among professionals – and accountants are likely to be some of the first to be affected, unless they focus on learning some new skills.

There are a few key intersecting technologies at the heart of this revolution. Artificial Intelligence (AI) is the most significant right now. This is the set of computing methods that allows for automated perception, learning, understanding and decision-making by machines.

AI is used in GPS systems to select the best route out of millions of options; it’s what allows Siri and Google Now to recognise our voice commands, and to translate what we say into other languages in real-time; it can recognise faces, see patterns in data, and ensures we get just the results we’re expecting from search engines, and receive recommendations at our favourite online stores and websites.

Each of these capabilities involves a complex network of microtasks, and it’s these small intelligent subsystems – called algorithms – that will start finding their way into our lives and our jobs in the near future.

The next level beyond this is machine learning or deep learning, where machines don’t simply complete tasks assigned to them but actually decide for themselves what the tasks should be. They’re sent in a general direction and make up the rules as they go along.

We are about a decade away from computers becoming more intelligent than we are, although they can already do many parts of our jobs better, faster and cheaper than we can now. This doesn’t mean we expect an army of sentient machines to invade our workplaces. Instead, slowly at first, and then increasingly bit by bit, our jobs will be eroded as machines do more and more of what we do today.

Machines are better
Machines are already better than humans at a whole range of tasks, including: predicting the weather, reading an X-ray, correcting grammar and spelling and checking for plagiarism, picking out a face in a crowd, storing and retrieving data, flying an airplane long distance, reading documents and doing discovery in a lawsuit, detecting a fire or a water leak, trading stocks and currencies, playing poker or chess, choosing what movie to watch next, auditing a bank statement, watering your garden, sorting packages, maintaining the correct temperature in your building, monitoring a critical care patient in hospital, eye surgery, and diagnosing cancer.

The last item on that list is interesting and provides a nice case study for CFOs to consider. IBM’s Watson computer – the third most powerful in the world – has spent the past few years learning about cancer and related diseases. It has access to more data than any human doctor ever has, and right now is outstripping human doctors in its ability to correctly diagnose diseases. Human doctors get about 75 percent of their diagnoses right, whereas Watson is close to 99 percent accurate with the same information. There is no doubt that if you had the choice, you’d want Watson to diagnose your disease. And if Watson is doing the diagnosis, then the machine might as well prescribe your treatment as well. What’s left for the human doctor to do?

The same is true for other professions – or will be as soon as large computers are focused on each of them. CFOs, for example, should all look at the audit software Auvenir, which has been making a splash at accounting conferences for the past two years. Using AI and blockchain technologies, it pretty much automates the audit process.

Key human skills
Over the next few years, we will see more and more work done by machines. But they won’t take all of the work from us – we will still need a few key human skills in the system. It is these skills that professionals should be focusing on if they want to remain relevant. Trying to beat the machines at the things they can do better than us is an exercise in futility.

Here are some of those skills:

1. Creativity and ingenuity. Coming up with novel ideas and new insights, and having the desire to do so, is something machines will battle to do. Computers can be taught the mechanics of originating new ideas but true creativity and new insights seem beyond their reach.

2. Sense-making. Too often the finance department appears to do little more than generate reports and summarise data – machines do that brilliantly. Analysis, insight and sense-making is what is required from people. The CFO of the future will use machines to crunch data but will rely on smart people to make sense of it all, to communicate it effectively, to engage with the business and to be thought leaders.

3. Unstructured problem-solving. Solving problems for which the rules do not currently exist. Many finance departments are gatekeepers of the company purse and manage the budget. They’ll need to become more proactive problem-solvers and bring strategic insights to the business to be relevant in the future.

4. Common sense. We typically call something ‘common sense’ when we put aside the strict and rigid application of rules, systems or logic and go with some form of gut instinct. In reality, we select one set of principles to trump another. It’s very difficult to write an algorithm for common sense, which is why most of us have experienced frustration already when we come up against automated systems. Humans are needed to help us escape from these rigid systems.

5. Ethics and morals. Many of the choices we make in life are made by balancing multiple sets of information and options. It’s not always obvious which choice is the right one. In legal terms, we talk about what the ‘reasonable man’ would do. It will be a long time before a machine masters the subtleties of doing this. An intelligent machine’s ‘moral code’ is only as good as the data it receives from humans – it doesn’t have metacognitive awareness itself.

6. Identifying errors. Whether it’s through programming mistakes or malicious cyber attacks, there is an almost certainty that AI won’t run entirely smoothly. To build AI systems that can identify errors in AI systems will take many decades, and so, for now, we’re going to have to rely on human beings to keep an eye on our machines to ensure they behave themselves.

7. Empathy, love, care and compassion. In many professions these traits are considered ‘soft skills’ but we know that it is these very human, relational traits that bond a team together and help motivate people to give above and beyond expectation. This includes self-awareness, personality and consciousness – three key things that science really battles to understand. The human touch is indispensable for most jobs – even in the finance department.

Intelligent technology can certainly improve human outcomes but it needs educated, imaginative and emotive humans to realise its full potential. For the foreseeable future at least, we need to partner with machines to make the most of the new world of work. And to make the most of our own personal careers and futures, we need to focus a lot more on developing the set of skills outlined above. These may not come naturally to many CFOs and their teams but mastering them will most certainly give you a competitive edge in the years ahead. In other words, CFOs should focus less on competing with machines and trying to do better what they can do best, and instead focus on becoming more human.

By Graeme Codrington

This article first appeared in CFO Magazine.

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Tags: ai, expert insight, futurist, graeme codrington, learning, machines, tomorrowtoday global

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