How might Scotland harness, and pioneer, Artificial Intelligence?
A summary landscape analysis of Artificial Intelligence and the massive potential it presents for Scotland.
Will Artificial Intelligence change the world?
The BBC asks ‘Why hasn’t AI changed the world yet?’ The MIT Technology Review defines what it can’t do yet.
In short we are still in the earliest days of what will be the most transformative technology ever developed, and Scotland with it’s deep history of invention and its’ extensive pedigree of academic expertise and active research in the fields of AI and Data Science, is ideally positioned to achieve a world leadership status.
Specific steps are being taken to carve out this capability, notably Scotland’s AI Strategy. Kate Forbes, Cabinet Secretary for Finance for the Scottish Government talks about what the AI strategy is and why AI in Scotland is important.
National AI Programs
First, for some landscape and context, we can consider the various national AI programs of some countries around the world.
At home here in the UK Diginomica reports that an advisory committee to the PM has released a report assessing the role of AI in government and has said that it does not believe there is a need for a new AI regulator, but that all current regulators must adapt to the challenges that AI poses to their specific sectors, adding that that the government is failing on openness and public sector organisations are not sufficiently transparent about their use of the technology.
In the USA the Whitehouse President Trump signed Executive Order 13859 announcing the American AI Initiative, which distinguishes the essential regions of AI that require Federal investments.
Released by the White House Office of Science and Technology Policy’s National Science and Technology Council, the Plan characterizes a few critical regions of priority for the Federal organizations that put resources into AI. They are considering providing AI for every field related to industries, workers, innovations etc.
A paper from the US think tank, the Center for Global Development, that was distributed back in July based on the potential impacts of AI and mechanical computerization on worldwide work markets. Analysts found that there isn’t enough work under process to go for the global automation fallout.
In Canada the CIO Council published a set of AI standards for responsible use of the technology. The non-profit association earned its accreditation to create National Standards of Canada from the Standards Council of Canada (SCC) this year. This council is based on four executive leaders, and around 40 members focused on ethical design and decision-making systems.
The need for ethical review of the technology is of course most acutely highlighted when we consider its’ military applications.
Line between warrior and machine blurs as China and U.S. military use artificial intelligence https://t.co/do63yBbiP0 #ai #artificialintelligence #MachineLearning #china #USA #military pic.twitter.com/DKxHUiutOJ
— Nige Willson (@nigewillson) March 11, 2020
Healthcare is an especially potent field for the application of AI. The demand on the sector grows massively while its’ capacity is severely challenged by issues like Brexit, and it requires the analytical processing of vast volumes of complex data. The WEF defines three ways AI will change healthcare by 2030.
With AI algorithms able to imitate human cognition in the analysis of complex medical data, AI is able to reveal patterns across large amounts of data that are excessively subtle or complex for people to identify. AI and predictive analysts help us to understand more about different factors in our lives that influence our health, not just when we might be ill, but even when we would also be going to get sick. AI algorithms might be able to detect human illness a month before being influenced.
Very timely examples include the Chinese tech giant Alibaba recently developing an AI system, and as per reports, they claim that this new system can detect Coronavirus in CT scans with 96% accuracy and, most of all, within just 20 seconds.
The system was prepared on images and information from 5,000 confirmed coronavirus cases and has only applied in medical clinics all over China. As indicated by the Review’s report, at least 100 healthcare facilities are, as of now, utilizing Alibaba’s AI.
In recently published research that sharpens focus on the intersection of machine intelligence and neuroscience, Purdue University researchers have designed how to decide what the human brain is seeing by using artificial intelligence technology to interpret Functional Magnetic Resonance Imaging (fMRI) scans from the people watching videos, representing a near of mind-reading tech.
The development, according to the researchers, could aid efforts to improve AI and lead to new insights into brain function. Critical to the research is a type of algorithm called a convolutional neural network, a form of deep learning algorithms, has been used to study how the brain processes static images.
The samples were used to train the convolution neural network model to estimate the activity in the brain’s visual cortex while the subjects were watching the videos.
Then they used the model to decode fMRI data from the issue to redesign the videos, even ones the model had never watched before. The model had the ability to decode the fMRI data accurately into specific image categories. Actual video images were then presented one-by-one with computers clarifying what the human brain saw based on fMRI data. From this they were able to find out how certain locations in mind were related to specific information a person can understand.
Enterprise AI – Industry 4.0
Similarly the potential for AI across business is vast. From factories to office work there is potential to achieve productivity improvements through intelligent automation, with different industries at different stages of adoption.
Enterprise AI is the capacity to insert AI technique – which joins the human capacities for learning, perception, and connection all at a degree of complexity that greatly augment our capabilities – into the very center of an organization’s information strategy.
Naturally sectors involved in repetitive manual tasks are ideal early use cases. IndustryWeek predicts 50% of manufacturing firms will use some form of AI robotics by the end of 2021, with the trend transforming the industry.
However this type of repetition inefficiency isn’t limited to factories, and we’re also seeing the rise of ‘virtual robots’ in the office too. ‘RPA’ is a form of business process automation technology that builds intelligent agents for that work by watching the user perform that task.
Any large organization, from Healthcare through Government, Banking and others, all suffer from huge bureaucracy workloads that this type of automation is ideal for.