1. Privacy: data is more quickly and easily exposed
AI systems need a lot of data. Often this includes personal data, for example customer data, user behavior or location information. This makes it extra attractive for hackers to steal this data. But things can go wrong even without malicious hackers: if data is not properly protected, or if data sets are worked with that still make people traceable, then there is a privacy risk.
What can you do?
- Keep track of what data you collect and use only what is really needed.
- Make data irreducible where possible (consider pseudonymization).
- Check regularly to make sure you are still in compliance with privacy regulations, such as the AVG.
- Be critical of who has access to what data within your organization.
2. AI can reinforce biases without you noticing it
AI learns from data you give it. If there is a skew in that, AI can unintentionally disadvantage certain groups. Imagine an AI that reviews resumes and unknowingly gives fewer opportunities to women or certain ages. Not only is that unfair, it can cause great damage to your reputation and even legal problems.
What can you do?
- Look closely at the data you are training AI with. Is it diverse enough?
- Regularly test whether decisions are fair and neutral.
- Involve different people in developing and assessing AI applications.
3. Deception by deepfakes and fake news is becoming increasingly realistic
AI makes it easy to fake images, videos and sounds. Think fake videos of politicians, or a fake voice pretending to be your boss. That makes phishing and social engineering much more dangerous. So you or your colleagues can become victims of fraud or make wrong decisions based on incorrect information just like that.
What can you do?
- Be critical of unexpected and suspicious messages, even if they seem genuine.
- Train yourself and your colleagues in recognizing fake content and social engineering (read how we do that here ).
- Use tools that can detect deepfakes and fake news.
4. AI decisions are not always fathomable
Sometimes you don't understand exactly why AI comes to a certain conclusion. This is called the "black box" problem. It causes you to have less grip on decisions, and makes it harder to spot errors or undesirable effects. Especially when it comes to sensitive issues, this can pose many risks.
What can you do?
- Whenever possible, choose AI systems that explain their choices ("explainable AI").
- Keep people involved in the process, especially in important decisions.
- Document what the AI does and check regularly to make sure everything is still correct.
5. AI systems themselves can be attacked
AI is not invulnerable. Techniques exist to mislead AI, for example by making small adjustments to inputs that cause AI to make wrong decisions. Hackers can also use AI to bypass security systems or extract sensitive data.
What can you do?
- Test AI systems for potential vulnerabilities.
- Make sure your software and models are always up to date.
- Integrate AI security into your broader cybersecurity strategy.
Responsible AI use with ISO 42001
The risks we discussed above show that AI offers opportunities but also brings new responsibilities. Fortunately, you don't have to organize that alone. There is now an international standard that helps you deploy AI safely and responsibly: ISO 42001.
This standard gives organizations a framework for managing AI applications in a way that is secure, fair and transparent. Think clear guidelines for ethics, privacy, security and reliability. By doing so, you reduce risk and show customers, partners and regulators that you are using AI seriously and responsibly.
Together with our partners Brush AI and Tidal Control, we support organizations in a successful ISO 42001 implementation. Want to know more? Read our story here.
How to get started today
These tips will help you keep a grip on your data, protect your privacy and avoid nasty surprises. You don't have to do it alone; enlisting the help of experts can give you a lot of peace of mind.
Want to know how AI can work safely and responsibly in your organization? Feel free to send us a message. Together we'll see what's best for you.
