is the only race that really matters,” Sundar Pichai, CEO of Google and Alphabet, said recently.
Although data-science leaders and teams are the experts in understanding how AI works, it’s important for all stakeholders to be involved in addressing these concerns. All employees should be aware of the ethical and legal considerations around AI and work together to ensure they are using it responsibly within an organisation.
To ensure transparency and accountability, organisations must make algorithms and correlations open to inspection so that participants can understand how their data is being used and how decisions are made. However, the complexity of machine learning and the popularity of deep-learning neural networks can make this challenging.
The final step is ensuring consumer privacy is preserved and respected, that consumers can opt out at any time, and that their data is only used for purposes they’ve consented to.The NIST special publication, “Towards a standard for identifying and managing bias in artificial intelligence”, points out that, while many organisations seek to utilise this information in a responsible manner, biases remain endemic across technology processes and can lead to harmful impacts, regardless of intent.
Earlier this month, Geoffrey Hinton, whose research into neural networks was pivotal to the creation of AI as we know it, and which saw him often called the “Godfather of AI”, left his role at the online search and advertising giant Google. Hinton said he left Google so that he could speak frankly about his concerns about the attendant risks of AI, rather than because of how Google is using it, but the move is concerning, nonetheless.
The risks of AI chatbots being exploited by malicious actors. For instance, using AI to create misinformation-spreading chatbots, using social media to manipulate electorates, or creating deepfakes.
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