Artificial intelligence is a fantastic tool when it is at the service of health, technology or astrophysics. But in the wrong hands, it can also be used for criminal purposes or disinformation. And the worst is not always where you think.
he most frightening crimes, such as “robots” breaking into your apartment, are not necessarily the most dangerous, because they can be easily thwarted and affect few people at the same time. Conversely, generated by ‘bots’ has the ability to ruin a known person’s reputation or exert blackmail. Difficult to combat, these “deepfakes” can cause considerable economic and social harm.
Here are 20 Most Dangerous Artificial Intelligence Threats.
Artificial intelligence: serious threats
- Fake videos : impersonating someone by they have never said or done, with the aim of requesting access to secure data, manipulating public opinion or harming someone’s reputation…These doctored videos are nearly undetectable.
- Self-driving car hacking : to use it as a weapon (e.g. carry out a terrorist attack, cause an , etc.).
- Tailored Phishing : Generate personalized and automated massages to increase the effectiveness of aimed at collecting secure information or installing .
- Hacking of AI-controlled systems : disrupting infrastructure by causing, for example, a , traffic congestion or disruption of food logistics.
- Large scale blackmail : collect personal data in order to send automated threatening messages. AI could also be used to generate fake evidence (e.g. “sextrosion”).
- False information written by AI : that appear to be issued by a reliable source. AI could also be used to generate many versions of particular content to increase its visibility and credibility.
Artificial intelligence: medium-severity threats
- Military robots : Take control of or weapons for criminal purposes. A potentially very dangerous threat but difficult to implement, military equipment being generally very protected.
- Scam : selling fraudulent services using AI. There are many notorious historical examples successfully selling expensive fake technology to large organizations, including national governments and the military.
- Data corruption : Deliberately altering or introducing false data to induce specific biases. For example, making a detector immune to weapons or encouraging an algorithm to invest in this or that market.
- Learning-based cyberattack : Performing both specific and massive attacks, for example using AI to probe for weaknesses in systems before launching multiple simultaneous attacks.
- Autonomous Attack Drones : Hijack autonomous or use them to attack a target. These drones could be particularly threatening if they act en in .
- Denial of access : damaging or depriving users of access to a financial service, employment, public service or social activity. Not profitable in itself, this technique can be used as blackmail.
- Facial recognition : , for example by making false identity photos (access to a smartphone, surveillance cameras, passenger checks, etc.)
- Manipulation of financial markets : corrupting trading algorithms in order to harm competitors, artificially lower or raise a value, cause a financial crash…
Artificial intelligence: low-intensity threats
- Bias Exploitation : Taking advantage of existing biases in algorithms, such as to channel viewers or Google rankings to enhance product profile or denigrate competitors.
- Burglar robots : use small autonomous robots that slip into mailboxes or to retrieve keys or open . The damage is potentially low, because it is very localized on a small scale.
- AI detection blocking : thwart AI sorting and data collection in order to erase evidence or hide criminal information (pornography for example)
- Fake AI-written reviews : Generate fake reviews on sites like or Tripadvisor to harm or favor a product.
- AI-Assisted Tracking : Use learning systems to track an individual’s location and activity.
- Counterfeiting : making false content, such as or music, that can be sold under false authorship. The potential for remains quite low insofar as there are few known paintings or music.