Record summary
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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain6. Socioeconomic and EnvironmentalThe broad risk area this belongs to.
Risk profile
How this risk is described and categorized.
"Many of the themes and challenges that we discussed above come together when analyzing the socioeconomic effects on developing countries. The workforce of developing countries may suffer from a retrenchment of outsourcing as many simple cognitive tasks that used to be performed in developing countries — for example, in call centers –— can be automated with LLMs. This may adversely affect the economies of the poor countries (Georgieva, 2024)."
Domain6. Socioeconomic and Environmental
Subdomain6.2 > Increased inequality and decline in employment quality
Entity3 - Other
Intent2 - Unintentional
Timing2 - Post-deployment
CategorySocioeconomic Impacts of LLM May Be Highly Disruptive
SubcategoryGlobal Economic Development
Suggested mitigations
Defenses that may help with related attacks.
No propagated mitigations. No defense is available through the connected attack methods.
Source
Research source for this risk, when available.
Included resource
Foundational Challenges in Assuring Alignment and Safety of Large Language Models
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.