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According to Gartner’s 2019 CIO Agenda survey, organisations that have deployed artificial intelligence (AI) grew from 4% to 14% between 2018 and 2019. Organisations are looking to take advantage of smart speakers such as Alexa and Google Home to provide another channel to market, and are rolling out chatbots as an alternative to call centre staff, to deal with common queries.
Thanks to the availability of AI frameworks, the barrier to entry for many organisations is quite low and developers can start building intelligence into their applications with little effort.
But the biggest stumbling block for many organisations is data. Unless the data is accurate and representative, then any data model derived from the dataset will be flawed. During 2019, there has been growing awareness of biases inherent in datasets that lead to flawed AI decision-making. Organisations, particularly the public sector and those in regulated industries, are also beginning to ask questions about how the AI made its decision, leading to greater emphasis on explainability.
These are Computer Weekly’s top 10 AI articles in 2019.
Why do systems that are supposed to help society seem to have a disproportionately adverse effect on ethnic minorities?
With so much artificial intelligence, machine learning and deep learning in development, we look at the kit programmers might find useful in their AI toolbox.
Devising compute strategies for AI applications can be challenging. Find out about the hardware, network and software frameworks available.
4. Gartner: Three barriers to AI adoption
CIOs are set to include artificial intelligence in their IT strategy. Technical, legislative and cultural challenges could influence their AI ambitions.
UK chipmaker Graphcore’s intelligence processing unit may just hold the key to unlocking the full potential of artificial intelligence.
The answer to the ultimate question of life, the universe and everything is 42, according to Deep Thought in The Hitchhiker’s Guide to the Galaxy – but experts need to explain AI decisions.
Latest forecasts suggest spending on artificial intelligence is ramping up, and organisations that need raw machine learning performance are turning to custom hardware.
For AI to improve our lives, it needs to reflect the real world, but regulating algorithms to be how we would like them to be risks introducing an unreality that makes them ineffective.
9. Gigging for robots
A few months ago, Automation Anywhere began collaborating with freelance software developer recruitment platform Toptal on robotic process automation in the human workforce. The concept is called the “digital worker”.
Study from McKinsey & Company finds data silos and a lack of enterprise integration are putting some industries at a disadvantage.