The Cyber Defense eMagazine November Edition for 2023

Charting a Trustworthy AI Journey
Sound cybersecurity principles for responsible generative AI innovation
By Lisa O’Connor, Managing Director—Accenture Security, Cybersecurity R&D, Accenture Labs
As companies turn to generative AI to transform business operations, traditional notions of trust are being
reshaped. How will the enterprise navigate a journey toward Responsible AI—designing, developing and
deploying AI in ways that engender confidence and trust?
AI brings unprecedented opportunities to businesses, but also incredible responsibility. Its direct impact
on people’s lives has raised considerable questions around AI ethics, data governance, trust and legality.
In fact, Accenture’s 2022 Tech Vision research found that only 35% of global consumers trust how AI is
being implemented by organizations. And 77% think organizations must be held accountable for their
misuse of AI.
That skepticism in understandable. Humans will have a more difficult time determining if sources of
information are reliable. There are risks that large language models will be used to manipulate data in
ways that will make us question the veracity of all sorts of information.
Today, threat actors are using Gen AI to write more and more effective phishing campaigns. They are
getting better at leveraging collected profiles and the troves of information we share on-line on social
sites to craft precision spearphishing. Attacks methods against AI and Generative AI are all over the dark
web. These methods take advantage of how these models work. For example “prompt injection” attacks
can cause the large language model (LLM) to unknowingly execute the malicious user’s instructions,
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