Record summary
A quick snapshot of what this page covers.
Risk profile
How this risk is described and categorized.
Algorithmic systems can increase “power imbalances in socio-economic relations” at the societal level [4, 137, p. 182], including through exacerbating digital divides and entrenching systemic inequalities [114, 230]. The development of algorithmic systems may tap into and foster forms of labor exploitation [77, 148], such as unethical data collection, worsening worker conditions [26], or lead to technological unemployment [52], such as deskilling or devaluing human labor [170]... when algorithmic financial systems fail at scale, these can lead to “flash crashes” and other adverse incidents with widespread impacts
Suggested mitigations
Defenses that may help with related attacks.
Source
Research source for this risk, when available.
Included resource
Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.