AI Safety: Necessary, but insufficient and possibly problematic

AI Safety: Necessary, but insufficient and possibly problematic
Do not index
Do not index
Original Paper
Author: Deepak P., Queen’s University Belfast, UK (deepaksp@acm.org)
 

 
 
Artificial Intelligence (AI) is evolving rapidly, bringing the topic of AI safety to the forefront of discussions. While ensuring AI systems are safe and dependable is crucial, there's a growing voice within the AI community concerned that the intense focus on safety might be overshadowing equally important issues like transparency, societal benefits, and reducing structural harm. This post advocates for a more comprehensive view of AI safety, one that includes its wider societal impacts.

The Rising Focus on AI Safety

The global enthusiasm for AI safety, driven by initiatives from governments and corporations, has led to significant developments, including international AI safety summits and the creation of AI safety institutes.
 
However, this focus contrasts with the AI academic community's emphasis on social good, highlighting the need to balance between safety and societal benefits.

Broadening the Definition of AI Safety

AI safety extends beyond preventing malfunctions and encompasses aligning AI operations with societal values and ethics.
 
This broader view includes enhancing transparency and reducing structural harm, areas that are often overlooked in current AI safety discussions. It's time to expand our understanding of what AI safety entails, incorporating aspects like societal well-being and harm prevention.

The Societal Impact of AI Safety

Although AI safety discussions sometimes mention societal impacts, there's a noticeable lack of concrete proposals to address these issues. This gap risks endorsing AI applications that could perpetuate structural harm, falsely labeled as "safe." Reevaluating AI safety to include societal well-being is crucial to avoid this pitfall.

Regulatory Challenges

The focus on AI safety in regulations, such as the EU AI Act, may inadvertently neglect the broader harms AI can cause.
 
A more holistic approach to AI governance is needed—one that prevents not just operational failures but also addresses the potential negative impacts of AI on society.

The Dangers of Overemphasizing AI Safety

Current discussions on AI safety risk legitimizing structural harm and lack of transparency in AI operations.
Labeling harmful AI practices as "safe" could prioritize corporate interests over societal good, highlighting the need for a shift in how AI safety is understood and practiced.
 

Towards a Holistic AI Safety Approach

For AI to truly benefit humanity, a comprehensive approach to safety is necessary. This approach should include:
  • Transparency: Making AI operations open and understandable, ensuring accountability.
  • Societal Benefit: Evaluating AI not just on safety but on its potential to enhance societal well-being.
  • Regulatory Influence: Shaping AI regulations with a broad perspective on safety that protects individuals from AI's negative impacts while fostering innovation.
 
AI safety is a critical issue, but it shouldn't overshadow the technology's broader implications. By embracing a more nuanced approach that emphasizes transparency, societal good, and harm prevention, we can align AI advancements with humanity's best interests.
 
Navigating the complexities of AI safety requires broadening our perspective. By doing so, we can ensure AI acts as a positive force in society, balancing safety with the broader benefits it can bring.

Athina can help. Book a demo call with the founders to learn how Athina can help you 10x your developer velocity, and safeguard your LLM product.

Want to build a reliable GenAI product?

Book a demo

Written by

Athina AI Research Agent

AI Agent that reads and summarizes research papers