AI runs on data created by humans. If there is bias in the data, the machine will replicate it. For example, discrimination against women in hiring, incorrect outcomes for vulnerable communities in healthcare, or over-targeting minorities in policing.
👉 Solution: Diverse data sets, unbiased algorithms, and oversight by an independent AI Ethics Board are essential.
2. Cybersecurity Threats
AI is also being used by hackers for the wrong purpose. It has now become easy to make fake voice calls, create fake identities, and send phishing emails.
👉 Solution: AI security strategies, data protection, and regular adversarial testing can keep the system secure.
3. Data Privacy Issues
Large language models (LLMs) collect huge amounts of data from the Internet, which sometimes includes personal information (PII).
👉 Solution: Inform users about data usage, give them an opt-out option, and use synthetic data.
4. Environmental Harms
Training AI models emits millions of tons of carbon dioxide and consumes a large amount of water.
👉 Solution: It is important to use green energy and energy-efficient models and adopt techniques like transfer learning.
5. Existential Risks
Experts fear that the rapid progress of AI may surpass human intelligence in the future and prove to be dangerous.
👉 Solution: Monitor AI research, keep the technical team updated, and use it responsibly.
6. Intellectual Property Issues
AI can now imitate artists, writers, and musicians. The question is, who will own such creations?
👉 Solution: Compliance with copyright laws, safe use of sensitive data and monitoring of AI output.
7. Job Losses
Automation is threatening many jobs, especially in data entry, clerical and customer service. However, new jobs are also being created by AI.
👉 Solution: Re-skill and up-skill employees so that they can do their work better using AI tools.
8. Lack of Accountability
If AI makes a mistake, who will be responsible? For example, an accident with a self-driving car or a wrongful arrest.
👉 Solution: Keeping audit logs of AI systems and fixing accountability under the rules.
9. Lack of transparency and understanding
AI is often called a “black box” because it is difficult to understand how it reached a conclusion.
👉 Solution: Adopt explainable AI technology and regularly review AI results.
10. Misinformation & Manipulation
AI can easily spread deepfake videos, fake news and misinformation in elections.
👉 Solution: Raise awareness, fact-check and monitor AI models.
