Once again Microsoft’s Future Decoded event turned out to be an amazing experience with many great insights from industry leaders, inspiring talks and informative sessions. This year it was all about AI.
The keynote on Day 1 was delivered by Cindy Rose OBE Microsoft UK CEO in which she raised many important questions: Are we ready for AI at scale? Are companies clear on the problem they are trying to solve with AI? Are employees involved in this journey? All those questions technology leaders should have answers to if they want to shift their AI initiatives from experimentation to implementation.
Cindy talked about the AI journey Microsoft has been on with some of its customers and the impressive impact it has had on their businesses and society.
East Suffolk and North Essex NHS Foundation Trust leverages AI and RPA (Robotic Process Automation) technology to relieve administrative burden and free up nurses’ time so that they can spend more time with the patients. It’s great to see this organisation trailblazing this space for healthcare and I hope there are more success stories like these to come.
I was particularly impressed with the story of WeWalk, a company which developed a “Smart Cane” for the visually impaired. Unlike a standard cane, this new device uses sensors to detect obstacles above chest level and of course it comes with a smartphone app. The app provides rich data services to the user, voice assistance, mapping services, improving users’ safety and mobility. WeWalk is a graduate of the Microsoft AI for Good accelerator programme and they leverage Azure AI services to process the data from the cane and use it to develop personalised mobility training programmes – pretty cool.
Another important matter discussed was AI Ethics. Microsoft takes this issue seriously and emphasises how important it is that organisations design these technologies in an ethical and unbiased way. Ethical frameworks around emerging technologies is a growing expectation by society, investors and customers and companies must be prepared to meet this demand.
Defining an AI strategy for Healthcare
Healthcare, with its vast amounts of data and chronic lack of time for anything, is one of the industries that needs technological improvements to be able to sustain itself. However, progress is slow – there is a lot of interest but little action. Perhaps healthcare organisations just don’t know where and how to start – they lack the strategy. The strategy recommended by Microsoft is based around the rule “think big but start small”. There are so many data touch points in healthcare, so many workflows, stakeholders and variables, it’s easy to get lost. Therefore, to reduce the risk of the project failing even before it starts, select one use case which can demonstrate the most value in a short period of time. Define the scenario and get clarity and understanding of the specific problem you are trying to solve. Consider how different users interact with each other, what is the end to end workflow and then scope minimum viable product. Microsoft has many great resources available to help organisations learn AI implementation best practice. One of them is the AI School which offers resources and case studies specific to the healthcare industry.
We all know having a strategy does not guarantee success; you also need people and their buy into your vision. A couple of most common concerns were raised that people may have when it comes to implementing AI technologies. Firstly, employees might fear AI will replace them in their jobs. I can understand that, but it all sounds a bit too futuristic to me. However, those concerns are real and the best way to address them is by “creating a culture of participation” – where employees are involved in their company’s AI journey right from the offset so that they can understand what the technology can and cannot do.
Secondly, what about the human element? As humans, we have a unique ability to understand context, show empathy and use intuition. Quite often this is needed in a healthcare setting and can’t be replaced by AI. To address this, it is important to make it clear that there are limitations to where AI can be used and it’s also technology providers’ responsibility to spread this message. In my view, while I can understand the need for the human element, this should not be the reason to simply say ‘AI will not work for us’. Also, what about human error? As humans we are prone to make mistakes and if AI can help us reduce them then I think it’s worth it.
Future Decoded showed some great examples of AI and its applications in healthcare and talked about important issues that surround this topic. Microsoft welcomes all AI initiatives in healthcare as one of its focus industries. I look forward to seeing the positive impact AI will have on healthcare organisations and delivering patient care. It seems that this time it’s more than just hype, AI just might be far more game changing than any other emerging technology.