Before organisations rush to exploit AI, they must be aware of the blind spots that can develop
It is fair to say that artificial intelligence (AI) is everywhere. Newspapers and magazines are littered with articles about the latest advancements and new projects being launched because of AI and machine learning (ML) technology. In the last year it seems like all of the necessary ingredients – powerful, affordable computer technologies, advanced algorithms, and the huge amounts of data required – have come together. We’re even at the point of mutual acceptance for this technology from consumers, businesses, and regulators alike. It has been speculated that over the next few decades, AI could be the biggest commercial driver for companies and even entire nations.
However, with any new technology, the adoption must be thoughtful both in how it is designed and how it is used. Organisations also need to make sure that they have the people to manage it, which can often be an afterthought in the rush to achieve the promised benefits.
Before jumping on the bandwagon, it is worth taking a step back, looking more closely at where AI blind spots might develop, and what can be done to counteract them.
The lack of ML Development
As the pace of AI and ML development intensifies alongside heightened awareness of cybercrime, organisations must ensure they take into account any potential liabilities. Despite this, it has been proven that security, privacy, and ethics are low-priority issues for developers when modelling their machine learning solutions.