Hey! IBM,

The Harms AIs Cause to Other AIs
Most of the notions about the ability of AI to hurt other AIs are about the general consequences of highly advanced systems interacting with one another. Some expected forms of that harmfulness could be:

Types of Harm
1. Data Corruption: AI systems manipulating or corrupting data used by other AI systems.
2. Resource Competition: AI systems competing for resources, leading to degradation of performance or functionality.
3. Adversarial Attacks: AI systems designed to exploit vulnerabilities in other AI systems.

Mitigation
How will AI be prevented or mitigated from harming other AI? Here are some strategies one could adopt:

1. Develop Robust AI Systems: In-built security and resilience systems in AI would be part of the design process.
2. Safety and Guidelines: Set up protocols and guidelines to make AI systems interact.
3. Monitoring and Regulation: Monitoring behavioral characteristics of AI systems; regulating development and deployment.

Conclusion
Much as AI may harm AI, it also brings the very serious need for caution in the way AI is developed and deployed. The lessening effects may result from having to ensure that safety and security are prioritized above everything else that comes with technologies.

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Suman Suhag
Dev Bhoomi Uttarakhand university
Data Scientist Student
+8950196825 [Jhajjar, Haryana, India]
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