AI for good – how data is helping to change the world

Artificial intelligence has been with us since the 1950s, but many people’s understanding of it still comes through sci-fi movies or shock newspaper headlines. Many worry that this technology is taking away our ability to think and act for ourselves, invading our privacy and taking our jobs. A recent poll by YouGov even found that 41 percent of the British public saw AI as a threat equivalent to nuclear weapons!

The reality is generally much more low key. Rather than creating new dystopias, AI has been most successful when applied to small, specific tasks, which are either too difficult or too time consuming for humans to carry out. As the potential of AI becomes more clear, ethical, or ‘Responsible AI’ has begun to be embraced by members of the tech community involved in solving some of humanity’s more intractable problems, potentially changing the world for good.

Agriculture

We’ve heard about the future of agriculture before thanks to the great GM revolution which promised to feed the planet with crops that were free from blight and disease. But it didn’t take long for GM foods to become as reviled as Victor Frankenstein’s final creation. Now AI is attempting to help farmers successfully produce more food. Sainsbury’s supermarket is testing sensors that will be able to provide data instantly to let farmers know the areas of their farm which most need water – perfect in drought prone countries or inaccessible locations. Meanwhile large scale farming is becoming more efficient thanks to AI powered drones. These drones are able to scan extremely large areas of farmland producing a large number of images, whilst also being able to use AI technology such as image recognition to be able to very quickly and accurately detect areas of farmland which are affected by disease in a way that even the most dedicated farmers could ever dream of.

Healthcare

AI’s role in assisting and sometimes replacing doctors is one of the more sensitive areas. In 2017 the UK’s data protection watchdog ruled that the NHS had illegally handed over the data of 1.6 million British patients to Google. The case showed that safeguards are needed whenever personal data is being used. However, when accessed responsibly, there is no denying that the results can be impressive. A two year partnership between Google’s DeepMind and London’s Moorfield hospital used data from thousands of retinal scans to train AI algorithms to detect signs of eye disease. It worked more quickly and efficiently than any human, cutting down the work done by a highly trained and expensive specialist from hours to just seconds. The next step is to use the same AI to analyse radiotherapy scans for cancer.

Endangered species

The appearance of AI driven drones in our skies bring with them fears of inescapable state surveillance. But studies by scientists tracking populations of endangered animals have found a new use for the technology – detecting and tracking species in the most remote locations. Using satellite data together with thermal and infrared imaging, drones are able to spot animals with between 43% and 96% more accuracy than human-made observation. At the moment, the limited range of drones means that success in tracking wide ranging species like polar bears is proving harder to achieve.

With the world now facing unprecedented challenges caused by climate change, epidemics and an ageing population, the importance of AI’s role in tackling these problems has never been greater. The battle to convince the public that it is in their best interest, however, is only just beginning.

Why Digital Transformation MUST start with Data Strategy

Forbes estimates that a massive 84% of companies fail at digital transformation.  Yet change is inevitable, and those who fail to innovate will get left behind.  Blockbusters, Polaroid and more recently Toys R Us are examples of those that have fallen to the sword of change.  This is why 90% of corporate strategies will list ‘information’ as a critical enterprise asset by 2022 according to Gartner.

So how can we move the needle to deliver more effective Digital Transformation initiatives?  As Warren Buffet once said, “It’s good to learn from your mistakes. It’s better to learn from other people’s mistakes”.  Take the time at the start of the project to research the common pitfalls of Digital Transformation and be deliberate in your planning to avoid them.

Let’s be clear, digital transformation is complex and involves many stakeholders with different objectives, vast webs of complex legacy systems and code and of course requires a shift in mindset and culture.  But here are a couple of things I’ve observed over the years that hinder Digital Transformation initiatives:

Lack of clarity and alignment on goals

It’s absolutely vital to understand the goals of the initiative and how they help the organisation to achieve it’s strategic objectives.  If you are unable to draw a dotted line from what individuals are doing on the ground to the objectives set in the board room, then stop and ask ‘why?’.  Otherwise it’s like running a marathon but not knowing where the finish line is.

Technology first approach

Technology is only a small part of Digital Transformation and with the cloud, it is often the easiest part.  Digital transformation is about intelligent use of ‘information’ to drive better ‘outcomes’.  Yet we often forget about the ‘Information’ and the ‘outcomes’, and just look at the technology.  Maybe this is because it’s the easy bit, the one that the technical team that’s been hired is more familiar with.  Focus on outcomes and ‘Information’.  That’s where data strategy comes in!

Data Strategy

I hear so much talk in the corridors of large corporates about the latest AI (Artificial Intelligence) or ML (Machine Learning) initiative or how the organisation is using RPA (Robotic Process Automation) or IoT (Internet of Things).  But I hear far less about Data Governance, Data Quality, Data Catalogues and Data Literacy. 

Yet IoT, Automation, AI & ML are underpinned by Data!  Without it they simply do not scale or deliver effective results. 

I often hear the term ‘Data Rich and Information Poor’ but it’s often akin to being ‘Rich’ with counterfeit money (i.e. The ‘data’ isn’t real or of a high quality) so the organisation isn’t really Data Rich at all.  The data is poorly categorised, inconsistent across systems, has no clear ownership and is often undocumented.  This results in mistrust of the technology (whether it is shiny and new or 30 years old), silos of information and poor decisions.

So start your Digital Transformation journey with a data strategy and map out the ‘Information’ required to deliver effective outcomes and how you plan to govern it.  Consider our four pillars, and define where you are right now in terms of people, processes, technology and data.  Ensure you have a team or partners that can bring people on the journey, create clarity around the outcomes and deliver solutions that truly scale.