Ethical Leadership and Governance

Meet the new design process: An upgrade with ethics & digital wellbeing baked in.

When consumers demand to see a positive impact from sustainable investments in their pensions by threatening to move $40 Trillion of assets, the investment industry will listen. In the very near future, the only investments that most people will make will be sustainable ones.

While there are real-world artificial intelligence (AI) applications for enterprises today, there is still much more potential and development for AI,

Technology in politics can be used either to sustain or to thwart democracy. IoT- and automation-enabled surveillance in China and Italy are grim warnings.

It’s notoriously difficult for organizations to keep faith with two equally important goals. A lot try. For-profit companies make grand pronouncements about social responsibility, but their resolve nearly always weakens when shareholder earnings are threatened.

Inclusive design expert Kat Holmes explains why the most effective business models, products and services address greatest variety of people.

It’s common practice for people’s data to be shared with partners of companies, etc. where individuals don’t understand who’s getting their data and why. Modern technology changes that, and it’s essential for all humans to have new tools so they can project their digital truth in the digital and algorithmic era.

It’s not the algorithm behaving badly, but how we define fairness that determines an artificial intelligence system’s impact.

Realizing the full potential of AI will take more than developing IT capabilities. The public must trust that its use will be both legal and ethical.

The digital revolution has brought in a new dimension to the challenge of ensuring responsible behaviour

Asking tech leaders how to regulate their own industry might be like “asking the foxes how best to guard the henhouse.”

With high-profile scandals and the seemingly daily buzz of breaches, scams and exploits, it’s more and more obvious that the data points that make up your online profiles are a hot commodity. Time for the citizenry to take back their personal data and bring back responsibility into the ecosystem.

Algorithms need training data to learn from. This training data is created, selected, collated and annotated by humans. And therein lies the problem.

The impression among business leaders is that ESG just hasn’t gone mainstream in the investment community. That perception is outdated

Should there be a moral imperative to consider what’s fair when making a business transaction?

Even governments in democracies with strong traditions of rule of law find themselves tempted to abuse these new abilities.

Artificial intelligence can play a powerful role in making the global economy more sustainable, through better monitoring, predicting problems in advance, and enabling the more efficient use of resources. And it can help the economy grow and create jobs at the same time, says a new report from PwC.

Tech companies need more than advisory boards if they want to create ethical products and services.

A new report says current initiatives to fix the field’s diversity crisis are too narrow and shallow to be effective.

Only a few legislators really know what they’re talking about, but it’s a start.

As big companies profit from our data, technological advances could make it so the control is taken back to the user and potentially, offer a new universal basic income at its heart.

The big tech business model by which users provide personal data in exchange of services is coming to crisis point, with data ownership under heavy scrutiny

It’s not easy to encourage the ethical use of artificial intelligence. But here are 10 recommendations.

Discussions of ethics in data science and artificial intelligence are all well and good, but they won't go anywhere if the prime directive is making massive profits for venture capitalists.

Big tech companies like Google and Microsoft have embraced AI ethics boards and charters, assuring the public that they’re essential to keeping the worst effects of machine learning in control. But are these projects actually helping anyone?