Responsible practices using tested processes must be the focus when creating new technology.
Technology has always been a double-edged sword. While it’s been a major force for progress, it has also been abused and caused harm. From steam power to Fordism, history shows that technology is neither good nor bad – by itself. It can, of course, be both, depending on how it’s used.
Telecommunications, specifically the intrnet, and more recently AI, which is estimated to contribute more than €11 illion to the global economy by 2030, are no diffrent.
On one hand, the internet connects us all – and kept us in touch with one another during the pandemic. AI and machine learning can help solve some of the world’s most pressing problems. Just a few examples are diagnosing disease, thwarting cyberattacks and fighting climate change. Yet, if left unchecked, algorithms can also perpetuate biases, create online echo-chambers, radicalisation and compromise safety and privacy.
2022 is poised to bring sweeping changes to digital regulations. The EU Parliament approved the Digital Services Act to increase online safety and consumer protection and is preparing the Artificial Intelligence Act to govern AI. The US Federal Trade Commission has published its guidance on AI, while China has launched a wave of regulations. The OECD currently tracks more than 700 AI policy initiatives across 60 countries.
Meanwhile, for years, the private and non-profit sectors have rallied behind the Tech for Good movement which strives to “put digital and technology at the service of humanity”. In its shortest and most sweeping form, it promises technology can help the world achieve the UN’s Sustainable Development Goals.
But in light of history, we must ask: Is it possible for Tech for Good to succeed without doing harm? We argue that the answer is largely about focusing on what we call “Good Tech”.
Good Tech prioritises processes before outcomes