Putting Ethics At The Heart Of AI, London – The future will be fashioned by artificial intelligence (AI). Governments are implementing advanced analytics and AI into their digital transformation plans, and AI already plays a major role in many industries. AI-enabled technology is changing how people interact both with business and the state.
Yet while there’s enormous potential for greater efficiency and better outcomes, pitfalls lie ahead if we aren’t careful. AI has the power to do huge amounts of good for humanity, but without high-quality data and human oversight, its decisions can become flawed. It’s important to follow best practices when building AI solutions to avoid inadvertently disadvantaging or excluding certain people and groups or misusing personal information.
AI is a form of advanced analytics – as such, many of the ethical concerns surrounding it have their roots in data. Data is the fuel that feeds AI, providing the raw information that machines need to analyze to help make decisions. That means that the foundation of good ethical AI is good ethical data and data handling practices. It’s possible to avoid ethical shortcomings in AI so long as a common, shared code of ethics can be established with data at the forefront.
A FATEful encounter
In a digital age, data is increasingly our most valuable asset. Yet it’s not just data that needs to be handled correctly – we also need to control how decisions are made using that data. It’s right and proper to demand it is treated ethically, but ethics is a question of personal values and, if not codified, it differs from person to person.
When agreeing on a common approach or framework for AI, it’s best to use those values we agree on as the founding principles. Debate is welcome and consensus will help employees and decision-makers support the guidelines in the future.
While it’s advisable for each organization to agree to its own code of AI ethics, it’s useful to have a set of core principles to work from. For example, the Government’s Data Ethics Framework provides general but strong guidelines to help public sector organizations use data responsibly. For AI and data science, the Fairness, Accountability, Transparency, And Explainability (FATE) framework provides an ideal starting point.
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