How to scale your AI use cases: A checklist
The business case for AI is realized when the application is scaled, not in the use cases of the pilot phase. Use the checklist below at the outset to ensure the transition...
Artificial Intelligence
AI and cybersecurity: Think like a thief to catch a thief
As digital tools become more sophisticated, it’s crucial to keep three key things in mind to protect your organization from cyber-attack.
1. Know AI’s capabilities and strengths so they can’t be used against you
Audio and video deepfakes can be used for fraud, phishing, and reputational damage. Executives should do two things to avoid being victimized:
- Learn about what’s possible with the latest digital technologies and AI.
- Have a secret codeword in place as an analog check in case of any doubts.
The basic lesson here is that, before launching their attacks, bad actors can gather a lot of information on your company and employees to find and exploit vulnerabilities. Prepare for this by putting some kind of multimodal authentication in place. The aim is twofold: to verify information that could be used to do harm, and keep that verification secret.
2. Know AI’s shortcomings and weaknesses so they can’t be used against you
Knowledge is power again here. There are all sorts of biases in AI (such as facial recognition technologies that recognize white faces with a higher degree of accuracy than black faces, and GenAI systems that read CVs differently depending on whether they are associated with male or female names.) Fix such biases by:
- Paying close attention to the training-data curation process.
- Putting carefully crafted governance mechanisms in place to mitigate the risks.
The lesson here is that even the most sophisticated GenAI tool is not foolproof. Companies must keep human beings in the loop to detect AI biases and blind spots, and have human oversight in their responsible AI governance processes.
3. Know that AI itself can be attacked
We are now seeing data-poisoning attacks where AI models are tricked into behaving badly. (This is a type of cyberattack in which an adversary intentionally compromises a training dataset used by an AI or machine-learning model to influence or manipulate it.) Hackers are also using “jailbreaking mechanisms” to evade the guardrails put in place to limit GenAI’s potential for harm. Two measures are useful to understand how AI systems can be attacked:
- Attend hackathons to equip yourself with the latest cyber-security measures.
- Invite digital experts to try to break your systems to find their vulnerabilities before actual cyber criminals do.
Key takeaway
By remaining vigilant and knowledgeable about AI’s strengths and weaknesses, organizations can mitigate risks. Think like your potential enemies to stay one step ahead in this new technological realm.
Authors
Related
What does a good AI use case look like?
With AI fever in overdrive, everyone is searching for winning AI use cases. However, the process feels like solving a giant jigsaw puzzle without a picture on the box to guide you....
Hacking Digital 4: How to work across silos
Working in silos is one of the biggest obstacles to digital success. The key to real digital transformation is to align the various business units in the organization. Here’s how to avoid...
Hacking Digital 3: How to develop digital skills within your organization
Learning new digital tools, technologies, and business models presents both short-term and longer-term challenges. Here’s a quick guide to the essentials of getting your people up to speed and beyond....