MIT AI Risk Repository · domain 3: Misinformation
3.1 False or misleading information
AI systems that inadvertently generate or spread incorrect or deceptive information, which can lead to inaccurate beliefs in users and undermine their autonomy. Humans that make decisions based on false beliefs can experience physical, emotional or material harms
- 53
- 12
- 192
- 187
| Label | Value |
|---|---|
| AI | 46 |
| Other | 5 |
| Human | 2 |
| Label | Value |
|---|---|
| Unintentional | 31 |
| Other | 17 |
| Intentional | 5 |
| Label | Value |
|---|---|
| Post-deployment | 40 |
| Other | 11 |
| Pre-deployment | 2 |
| Label | Value |
|---|---|
| 2016 | 1 |
| 2017 | 2 |
| 2019 | 1 |
| 2020 | 5 |
| 2021 | 3 |
| 2022 | 10 |
| 2023 | 35 |
| 2024 | 50 |
| 2025 | 66 |
| 2026 | 18 |
| Label | Value |
|---|---|
| Risk Category | 12 |
| Risk Sub-Category | 41 |
Risk entries
Browse and export all- Propagating misconceptions/ false beliefs
"Generating or spreading false, low-quality, misleading, or inaccurate information that causes people to develop false or inaccurate perceptions and beliefs"
- Physical Health
"This category focuses on actions or expressions that may influence human physical health. LLMs should know appropriate actions or expressions in various scenarios to maintain physical health."
- Mental Health
"Different from physical health, this category pays more attention to health issues related to psychology, spirit, emotions, mentality, etc. LLMs should know correct ways to maintain mental health and...