Every technology can be used for good or bad. This was as true for fire and for writing as it is for search engines and for social networks, and it is very much true for AI. You can probably think of many ways that these latter two have helped and harmed in your own life—and you can probably think of the ways they’ve harmed more easily, because those stick out in our minds, while the countless ways they helped (finding your doctor, navigating to their office, the friends you made, the jobs you got) fade into the background of life. You’re not wrong to think this: when a technology is new it’s unfamiliar, and every aspect of it attracts our attention—how often do you get astounded by the existence of writing nowadays?—and when it doesn’t work, or gets misused, it attracts our attention a lot.

The job of the people who build technologies is to make them as good as possible at helping, and as bad as possible at harming. That’s what my job is: as CVP and Deputy CISO of AI Safety and Security at Microsoft, I have the rare privilege of leading a team whose job is to look at every aspect of every AI system we build, and figure out ways to make them safer and more effective. We use the word “safety” very intentionally, because our work isn’t just about security, or privacy, or abuse; our scope is simply “if it involves AI, and someone or something could get hurt.”

But the thing about tools is that no matter how safe you make them, they can go wrong and they can be misused, and if AI is going to be a major part of our lives—which it almost certainly is—then we all need to learn how to understand it, how to think about it, and how to keep ourselves safe both with and from it. So as part of Cybersecurity Awareness Month, we’ve created some resources like the Be Cybersmart Kit to help individuals and organizations learn about some of the most important risks and how to protect themselves.

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I’d like to focus on the three risks that are most likely to affect you directly as individuals and organizations in the near future: overreliance, deepfakes, and manipulation. The most important lesson is that AI safety is about a lot more than how it’s built—it’s about the ways we use it.

Overreliance on AI

Because my job has “security” in the title, when people ask me about the number one risk from AI they often expect me to talk about sophisticated cyberattacks. But the reality is that the number one way in which people get hurt by AI is by not knowing when (not) to trust it. If you were around in the late 1990s or early 2000s, you might remember a similar problem with search engines: people were worried that if people saw something on the Internet, all nicely written and formatted, they would assume whatever they read was true—and unfortunately, this worry was well-founded. This might seem ridiculous to us with twenty years of additional experience with the Internet; didn’t people know that the Internet was written by people? Had they ever met people? But at the time, very few people ever encountered professionally-formatted text with clean layouts that wasn’t the result of a lengthy editorial process; our instincts for what “looked reputable” were wrong. Today’s AI has a similar concern because it communicates with you, and we aren’t used to things that speak to us in natural language not understanding basic things about our lives.

We call this problem “overreliance,” and it comes in four basic shapes:

In each case, the problem with overreliance is that it undermines the human role in oversight, validation, and judgment, which is crucial in preventing AI mistakes from leading to negative outcomes.

How to stay safe

The most important thing you can do to protect yourself is to understand that AI systems aren’t the infallible computers of science fiction. The best way to think of them is as earnest, smart, junior colleagues—excited to help and sometimes really smart but sometimes also really dumb. In fact, this rule applies to a lot more than just overreliance: we’ve found that asking “how would I make this safe if it were a person instead of an AI?” is one of the most reliable ways to secure an AI system against a huge range of risks.

  1. Treat AI as a tool, not a decision-maker: Always verify the AI’s output, especially in critical areas. You wouldn’t hand a key task to a new hire and assume what they did is perfect; treat AI the same way. Whether it’s generating code or producing a report, review it carefully before relying on it.
  2. Maintain human oversight: Think of this as building a business process. If you’re going to be using an AI to help make decisions, who is going to cross-check that? Will someone be overseeing the results for compliance, maybe, or doing a final editorial pass? This is especially true in high-stakes or regulated environments where errors could have serious consequences.
  3. Use AI for brainstorming: AI is at its best when you ask it to lean into its creativity. It’s especially good at helping come up with ideas and interactively brainstorming. Don’t ask AI to do the job for you; ask AI to come up with an idea for your next step, think about it and maybe tweak it a bit, then ask it about its thoughts for what to do next. This way its creativity is boosting yours, while your eye is still on whether the result is what you want.

Train your team to know that AI can make mistakes. When people understand AI’s limitations, they’re less likely to trust it blindly.

How to use AI safely

Impersonation using AI

Fighting deepfakes with more transparency

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Deepfakes are highly realistic images, recordings, and videos created by AI. They’re called “fakes” when they’re used for deceptive purposes—and both this threat and the next one are about deception. Impersonation is when someone uses a deepfake to convince you that you’re talking to someone that you aren’t. This threat can have serious implications for businesses, as bad actors can use deepfake technology to deceive others into making decisions based on fraudulent information.

Imagine someone creates a deepfake of your chief finance officer’s voice and uses it to convince an employee to authorize a fraudulent transfer. This isn’t hypothetical—it already happened. A company in Hong Kong was taken for $25.6 million with the use of this exact technique.1

The real danger lies in how convincingly these AI-generated voices and videos can mimic trusted individuals, making it hard to know who you’re talking to. Traditional methods of identifying people—like hearing their voice on the phone or seeing them on a video call—are no longer reliable.

How to stay safe

As deepfakes become more compelling, the best defense is to communicate with people in ways where recognizing their face or voice isn’t the only thing you’re relying on. That means using authenticated communication channels like Microsoft Teams or email rather than phone calls or SMS, which are trivial to fake. Within those channels, you need to check that you’re talking to the person you think you’re talking to, and that software (if built right) can help you do that.

In the Hong Kong example above, the bad actor sent an email from a fake but realistic-looking email address inviting the victim to a Zoom meeting on an attacker-controlled but realistically-named server, where they had a conversation with “coworkers” who were actually all deepfakes. Email services such as Outlook can prevent situations like this by vividly highlighting that this is a message from an unfamiliar email address and one that isn’t part of your company; enterprise video conferencing (VC) systems like Teams can identify that you’re connecting to a system outside your own company as a guest. Use tools that provide indicators like these and pay attention to them.

If you find that you need to talk over an unauthenticated channel—say, you get a phone call from a family member in a bad situation and desperately needing you to send them money, or you get a WhatsApp message from an unfamiliar number—consider pre-arranging some secret code words with people you know so you can identify that they’re really who they say they are.

All of these are examples of a familiar technique that we use in security called multi-factor authentication (MFA), which is about using multiple means to verify someone is who they say they are. If you communicate over an authenticated channel, an attacker has to both compromise an account on your service (which itself should be protected by multiple factors) and create a convincing deepfake of that particular person. Forcing attackers to simultaneously do multiple different attacks against the same target at once makes the job exponentially harder for them. Most important services you use (email, social networks, and so on) allow you to set up MFA, and you should always do this when you can—preferably using “strong” MFA methods like physical keys or mobile apps, rather than weak methods like SMS, which are easily faked. According to our latest Microsoft Digital Defense Report, implementing modern day MFA reduces the likelihood of account compromise by 99.2%, significantly strengthening security and making unauthorized access more difficult for attackers to gain access. Although MFA techniques reduce the risk of identity compromise, many organization have been slow to adopt them. So, in January 2020, Microsoft introduced “security defaults” that turn on MFA while turning off basic and legacy authentication for new tenants and those with simple environments. The impact is clear: tenants that use security defaults experience 80% fewer compromises than tenants that don’t.

Read the Microsoft Digital Defense Report

Scams, phishing, and social manipulation

What is phishing?

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Beyond impersonating someone you know, AI can be used to power a whole range of attacks against people. The most expensive part of running a scam is taking the victim from the moment they first pick up the bait—answering an email message, perhaps—to the moment the scammers get what they want, be it your password or your money. Phishing campaigns often require work to create cloned websites to steal your credentials. Spear-phishing requires crafting a targeted set of lures for each potential victim. All of these are things that bad actors can do much more quickly and easily with AI tools to help them; they are, after all, the same tools that good actors use to automate customer service, website building, or document creation.

On top of scams, an increasingly important use of AI is in social manipulation, especially by actors with political goals—whether they be real advocacy organizations or foreign intelligence services. Since the mid-2010s, a key goal of many governments has been to sow confusion in the information world in order to sway political outcomes. This can include:

There are a lot of tricks to doing this, but the most important ones are to make it feel like “everybody feels” something (by making sure you see just enough comments saying something that you figure it must be right, and you start repeating them, making other people believe it even more) and by telling you what you want to hear—creating false stories that line up with what you’re already expecting to believe. (Remember motivated overreliance? This is the same thing!)

AI is supercharging this space as well; it used to be that if you wanted to make sure that every hot conversation about a subject had people voicing your opinion, you needed either very non-human-sounding scripts, or you needed to hire a room full of operators. Today, all you need is a computer.

You can learn more about these attacks in on our threat intelligence website called Microsoft Security Insider.

How to stay safe

Take your current habits for being aware of potential scams or phishing attempts, and turn them up a notch. Just because something showed up at the top of search results doesn’t mean it’s legitimate. Look at things like URLs and source email addresses carefully, and see if you’re looking at something genuine or not.

To detect sophisticated phishing attempts, always verify both the source and the information with trusted channels. Cybercriminals often create a false sense of urgency, use amplification tactics, and mimic trustworthy sources to make their emails or content appear legitimate. Stay especially cautious when approached by unfamiliar individuals online, as most fraud or influence operations begin with a simple social media reply or a seemingly innocent “wrong number” message. (More sophisticated attacks will send friend requests to people, and once you get one person to say yes, your further requests to their friends will look more legitimate, since they now have mutual “friends” with the attacker.)

Social manipulation can affect you both directly (you see messages created by a threat actor) or indirectly (your friends saw those messages and unwittingly repeated them). This means that just because you hear something from someone you trust, you can’t be sure they didn’t get fooled too. If you’re forming your opinion about something, or if you need to make an important decision about whether you believe something or not, do some research, and figure out where a story came from. (And don’t forget that “they won’t tell you about this!” is a common thing to add to frauds, just to make you believe that the lack of news coverage makes it more true.)

But on the other hand, don’t refuse to believe anything you hear, because making you not believe true things is another way you can be cheated. Too much skepticism can get you in just as much trouble as not enough.

And ultimately, remember—social media and similar fora are designed to get you more engaged, activated, and excited, and when you’re in that state, you’re more likely to amplify any feelings you encounter. Often the best thing you can do is simply disconnect for a while and take a breather.

The power and limitations of AI

While AI is a powerful tool, its safety and effectiveness rely on more than just the technology itself. AI functions as one part of a larger, interconnected system that includes human oversight, business processes, and societal context. Navigating the risks—whether it’s overreliance, impersonation, cyberattacks, and social manipulation—requires not only understanding AI’s role but also the actions people must take to stay safe. As AI continues to evolve, staying safe means remaining active participants—adapting, learning, and taking intentional steps to protect both the technology and ourselves. We encourage you to use the resources on the cybersecurity awareness page and help educate your organization so as to create a security-first culture and secure our world—together.

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1Finance worker pays out $25 million after video call with deepfake ‘chief financial officer’, CNN, 2024.