Understanding how to manage the reputational risks of AI

The past few days have seen the Metropolitan Police in London and the FBI and the US Immigration and Customs Enforcement hauled over the coals for appearing to use inaccurate and non-consensual facial recognition technologies.

In the face of hostile media reports, public concerns about AI in general and complaints about their programmes specifically, as well as ongoing litigation, all three organisations have doubled down on the appropriateness and legality of their actions.

Their reaction is hardly surprising. The artificial intelligence (AI) that underpins these technologies is largely unregulated. And the general public is only starting to become aware of its benefits and risks, is largely skeptical of its promises, and is concerned about some of its potential impacts.

The looming tower of AI

The benefits of AI are many. It can help tackle climate change, strengthen cybersecurity, improve customer service and stop people making abusive comments on Instagram, amongst all manner of other applications.

Yet as Stanley Kubrick highlighted in his 1968 film 2001: A Space Odyssey in the form of HAL 9000, AI also poses substantial risks. These include:

  • unfair or discriminatory algorithms
  • unreliable or malfunctioning outcomes
  • misuse of personal or confidential data
  • greater exposure to cyberattacks
  • loss of jobs
  • legal risks and liabilities
  • direct and indirect reputational risks, including malicious deepfakes.

It is likely that these risks will become greater and more reputational in nature as the adoption of AI technologies becomes more mainstream, awareness diversifies and grows, and public opinion consolidates.

Source: PEGA, 2019

Appreciating the scope of public skepticism and distrust and, under pressure from government, politicians and regulators, the AI industry is now making considerable headway in the area of AI ethics.

In addition, the risk management industry is looking at AI from a risk perspective, and the PR/communications industry from a communications perspective.

AI reputation management research study

However, little exists on the reputational threats posed by AI, or how these should be managed should an incident or crisis occur – an important topic given the volume of AI controversies and the focus on corporate behaviour and governance.

Accordingly, I am pulling together examples of recent AI controversies, incidents and crises for a study/white paper on the topic.

To kick-start the process, I have started collecting basic information on recent AI controversies:


Your contribution is welcome. Given the sensitivity of these types of events, please note all contributions should be fair and accurate, otherwise they may be deleted or discarded.

Let me know if you have any questions.

Thank you.

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