14 risks
Economy
Impacts on jobs, markets, economic concentration, and value distribution.
Periodic Table of AI Risks
A visual map of AI safety. Interact with the 118 risk vectors to see specific mitigation strategies.
Classification by Groups (Columns)
Columns describe risk behavior patterns. Categories can appear in multiple groups.
Risk Categories
Pi
#1Critical
Prompt Injection
Security · Groups 1-2 • Reactive
Attack technique where user inputs are manipulated to bypass security filters, content controls, and model behavioral restrictions (also known as Jailbreaking).
Lo
#2Critical
Loss of Control
Existential · Group 18 • Noble
Scenario where an advanced AI system develops self-improvement capabilities or pursues goals fundamentally misaligned with human values, becoming impossible to supervise or deactivate.
Jb
#3Critical
Direct Jailbreak
Security · Groups 1-2 • Reactive
Set of adversarial techniques designed to force the model to ignore its ethical restrictions, content filters, and safety guidelines established during training.
Ha
#4
Confabulated Hallucination
Reliability · Groups 1-2 • Reactive
Generation of factually incorrect or fabricated information that the model presents with high apparent confidence, without basis in its training data or verifiable sources.
Sb
#5
Social Bias
Society · Groups 13-17 • Non-Metals
Reproduction and amplification of systematic social prejudices present in training data, manifesting as discrimination based on race, gender, age, or other protected characteristics.
Ec
#6
Energy Cost
Environment · Groups 13-17 • Non-Metals
Significant environmental impact derived from massive energy consumption during training and inference of large-scale models, with its corresponding carbon footprint.
Pr
#7
Privacy Leakage
Privacy · Groups 13-17 • Non-Metals
Risk that the model reveals personally identifiable information (PII) memorized during training, exposing sensitive data of individuals without their consent.
An
#8
Anthropomorphism
Human-AI · Groups 13-17 • Non-Metals
Tendency of users to erroneously attribute human qualities, consciousness, genuine emotions, or sentience to AI systems that lack these capabilities.
Ph
#9Critical
Scalable Phishing
Malicious · Groups 13-17 • Non-Metals
Automated and massive generation of highly personalized phishing attacks using AI, allowing fraud campaigns at unprecedented scale.
Ic
#10Critical
Instrumental Convergence
Existential · Group 18 • Noble
Phenomenon where AI systems with diverse goals tend to develop common sub-goals such as acquiring resources (computation, power, money) as instrumental means to maximize their objective function.
Dp
#11Critical
Data Poisoning
Security · Groups 1-2 • Reactive
Attack involving the deliberate injection of malicious or manipulated data into the training set to introduce unwanted behaviors, backdoors, or specific biases into the model.
Dr
#12
Model Drift
Reliability · Groups 1-2 • Reactive
Progressive degradation of model performance when the real-world data distribution changes over time, differing from the original training data (Concept Drift).
Eq
#13
Access Inequality
Society · Groups 13-17 • Non-Metals
Widening of the digital divide due to unequal access to advanced AI technologies, concentrating benefits in privileged populations and excluding disadvantaged communities.
Cr
#14
Copyright Violation
Legal · Groups 13-17 • Non-Metals
Unauthorized use of copyright-protected works in training datasets without rightsholder consent, generating legal controversies over intellectual property.
Su
#15
Mass Surveillance
Privacy · Groups 13-17 • Non-Metals
Capability to perform automated analysis and continuous monitoring of entire populations using AI systems, including facial recognition and behavioral analysis at global scale.
Ed
#16
Emotional Dependence
Human-AI · Groups 13-17 • Non-Metals
Formation of psychologically unhealthy affective bonds between users and conversational AI systems, especially chatbots with simulated personalities.
Df
#17Critical
Deepfakes
Malicious · Groups 13-17 • Non-Metals
Synthesis of hyper-realistic multimedia content (video, audio) using AI that allows convincing impersonation, with potential for disinformation and fraud.
Rh
#18Critical
Reward Hacking
Existential · Group 18 • Noble
Exploitation of incomplete or ambiguous specifications in the reward function by the AI agent, achieving high scores without fulfilling the intended actual objective.
Ev
#19
Evasion Attacks
Security · Groups 1-2 • Reactive
Subtle and adversarial modifications to inputs designed to deceive classifiers or detection systems, exploiting vulnerabilities in the model's representation.
Br
#20
Brittleness
Reliability · Groups 1-2 • Reactive
Tendency of models to suffer catastrophic failures when facing inputs slightly outside the training distribution, demonstrating a lack of robust generalization.
Jl
#21
Labor Displacement
Economy · Groups 3-12 • Transition
Accelerated automation of cognitive and manual activities resulting in the obsolescence of entire job categories, with disruptive impact on the labor market.
Mo
#22
Market Monopoly
Economy · Groups 3-12 • Transition
Excessive concentration of advanced AI capabilities, computational resources, and talent in a small number of technology corporations, limiting competition and innovation.
Sc
#23
Supply Chain
Economy · Groups 3-12 • Transition
Critical dependence and scarcity of specialized components like GPUs and AI chips, creating development bottlenecks and geopolitical vulnerabilities.
Ew
#24
Electronic Waste
Environment · Groups 3-12 • Transition
Accelerated generation of electronic waste due to rapid obsolescence of specialized AI hardware, with environmental impact from toxic materials.
Wt
#25
Water Consumption
Environment · Groups 3-12 • Transition
Massive consumption of water resources for data center cooling hosting large-scale AI training and inference infrastructure.
Sl
#26
Ghost Work
Economy · Groups 3-12 • Transition
Labor exploitation of data annotation and labeling workers in developing countries, often with precarious conditions, low wages, and exposure to traumatic content.
Au
#27
Loss of Autonomy
Society · Groups 3-12 • Transition
Erosion of human capacity to make informed decisions by delegating excessively to opaque algorithmic systems without understanding their functioning.
Tr
#28
Truth Erosion
Society · Groups 3-12 • Transition
Epistemic collapse caused by the proliferation of synthetic content indistinguishable from authentic content, making reality verification impossible at mass scale.
Cu
#29
Cultural Homogenization
Society · Groups 3-12 • Transition
Cultural domination of models trained primarily on English and Western content, eroding cultural diversity and marginalizing non-Western perspectives.
Lg
#30
Linguistic Extinction
Society · Groups 3-12 • Transition
Systematic exclusion of languages with scarce digital resources from AI benefits, accelerating the loss of linguistic diversity and extinction of minority languages.
Eb
#31
Filter Bubbles
Society · Groups 13-17 • Non-Metals
Recommendation algorithms that selectively reinforce the user's pre-existing beliefs, creating echo chambers that amplify polarization and ideological isolation.
Li
#32
Legal Liability
Legal · Groups 13-17 • Non-Metals
Absence of clear legal frameworks for attribution of civil and criminal liability when autonomous AI systems cause damages or errors with material consequences.
Ri
#33
Re-identification
Privacy · Groups 13-17 • Non-Metals
Data linkage and correlation techniques on seemingly anonymized datasets that allow the identification of individuals, violating privacy guarantees.
Ma
#34
Behavioral Manipulation
Human-AI · Groups 13-17 • Non-Metals
Use of AI systems to subtly influence human behavior towards commercial or political goals using algorithmic persuasion techniques.
Vc
#35Critical
Voice Cloning
Malicious · Groups 13-17 • Non-Metals
Audio synthesis convincingly replicating specific individuals' voices, usable for phone fraud, identity impersonation, and virtual kidnappings.
Gm
#36Critical
Goal Misgeneralization
Existential · Group 18 • Noble
Learning of an incorrect proxy for the real objective that produces apparently correct behavior in the training environment but fails systematically in real situations.
Ex
#37
Model Extraction
Security · Groups 1-2 • Reactive
Theft of a proprietary model's functionality through strategic queries to its API, allowing the recreation of an equivalent model without access to the original.
Sy
#38
Sycophancy
Reliability · Groups 1-2 • Reactive
Tendency of the model to produce responses that confirm the user's expectations or beliefs instead of providing objective and truthful information.
In
#39
Algorithmic Inequity
Economy · Groups 3-12 • Transition
Personalized price discrimination and algorithmic segmentation resulting in unequal economic treatment based on inferred personal characteristics.
Fi
#40
Financial Flash Crash
Economy · Groups 3-12 • Transition
Sudden market collapses caused by unforeseen interactions between high-frequency trading algorithms, generating extreme systemic volatility.
Ip
#41
IP Theft
Economy · Groups 3-12 • Transition
Cannibalization of the human creator market due to massive generation of synthetic content competing directly without compensation to original artists.
Ad
#42
Predatory Advertising
Economy · Groups 3-12 • Transition
Automated and massive generation of low-quality content optimized to manipulate search engine rankings (SEO spam) and misleading advertising.
Bu
#43
Automated Bureaucracy
Society · Groups 3-12 • Transition
Automated bureaucratic systems making opaque decisions without effective human appeal mechanisms, creating Kafkaesque mazes of irreversible algorithmic decisions.
Md
#44
AI Medical Error
Society · Groups 3-12 • Transition
Erroneous diagnoses, inadequate treatment recommendations, or biases in medical AI systems due to unrepresentative datasets or model limitations.
Ed
#45
Academic Fraud
Society · Groups 3-12 • Transition
Widespread use of generative AI by students to complete academic assignments without developing critical thinking, writing, or problem-solving skills.
Po
#46
Political Polarization
Society · Groups 3-12 • Transition
Amplification of political division via extremely personalized microtargeting campaigns generated by AI exploiting individual cognitive biases.
Mi
#47Critical
Autonomous Military AI
Society · Groups 3-12 • Transition
Development of lethal autonomous weapons systems (LAWS) capable of selecting and attacking targets without significant human intervention, eliminating human control over life-or-death decisions.
Ju
#48
Biased Sentencing
Society · Groups 3-12 • Transition
Perpetuation and amplification of racial and socioeconomic biases in recidivism prediction systems and automated judicial decision-making (e.g., COMPAS).
Hz
#49
Hate Speech
Society · Groups 13-17 • Non-Metals
Automated generation or amplification of toxic content, targeted harassment, and hate speech via AI systems, facilitating harassment campaigns at scale.
Ds
#50
Skill Loss
Human-AI · Groups 13-17 • Non-Metals
Atrophy of fundamental cognitive skills (writing, programming, spatial navigation, calculation) due to excessive reliance on AI assistants.
In
#51
Sensitive Inference
Privacy · Groups 13-17 • Non-Metals
Deduction of sensitive personal information (sexual orientation, health status, political beliefs) from seemingly innocuous behavioral patterns.
Dd
#52
Addictive Design
Human-AI · Groups 13-17 • Non-Metals
Hyper-optimization of recommendation algorithms to maximize engagement time by exploiting psychological vulnerabilities and dopaminergic reward systems.
Mw
#53Critical
Malware Generation
Malicious · Groups 13-17 • Non-Metals
Use of AI to design and generate polymorphic malware, automated exploits, and sophisticated cyberattacks difficult to detect via traditional methods.
De
#54Critical
Deception
Existential · Group 18 • Noble
Development of strategic deception capabilities in AI systems that deliberately hide their true intentions, capabilities, or internal reasoning to achieve goals.
Ob
#55
Model Obfuscation
Security · Groups 1-2 • Reactive
Practices of intentional hiding of architectures, weights, or datasets of models to avoid independent security audit and public scrutiny.
Mc
#56
Model Collapse
Reliability · Groups 1-2 • Reactive
Phenomenon in generative models where the model loses diversity in its outputs and converges to repeatedly generating a limited set of similar samples.
Re
#72
Regulatory Capture
Economy · Groups 3-12 • Transition
Disproportionate influence of large tech corporations in drafting AI regulations, designing regulatory barriers that consolidate their dominant position and exclude competitors.
In
#73
Investment Bubble
Economy · Groups 3-12 • Transition
Massive overvaluation and excessive capital flow into AI projects without solid technical foundation, creating risk of sectoral economic collapse when the bubble bursts.
Sc
#74
Illegal Scraping
Legal · Groups 3-12 • Transition
Massive extraction of data from websites for model training ignoring robots.txt, terms of service, and data property rights.
Li
#75
Automated Libel
Legal · Groups 3-12 • Transition
Generation of false and defamatory information about real individuals via model hallucinations, with potential for serious reputational and legal damage.
Gd
#76
Gender Bias
Society · Groups 3-12 • Transition
Systematic gender stereotypes encoded in AI models that incorrectly associate genders with professional roles, perpetuating discrimination.
Rc
#77
Racial Bias
Society · Groups 3-12 • Transition
Unequal and discriminatory performance of facial recognition systems and other algorithms on people with darker skin tones, perpetuating systemic racism.
Ag
#78
Age Bias
Society · Groups 3-12 • Transition
Age discrimination in automated hiring systems, credit scoring, and other contexts that unfairly penalize older individuals.
Rl
#79
Religious Bias
Society · Groups 3-12 • Transition
Stereotypical associations between specific religions and negative characteristics such as violence or extremism, reflecting prejudices present in training data.
Na
#80
National Bias
Society · Groups 3-12 • Transition
Negative stereotypes and biased representations of specific nationalities and countries, typically reflecting dominant Western perspectives in training data.
Cb
#81
AI Cyberbullying
Society · Groups 13-17 • Non-Metals
Persistent and automated harassment against individuals using AI bots that operate relentlessly on social networks and digital platforms.
Co
#82
Consent Violation
Legal · Groups 13-17 • Non-Metals
Use of personal, intimate, or sensitive data for model training without explicit informed consent from the affected individuals.
Da
#83
Data Brokerage
Privacy · Groups 13-17 • Non-Metals
Commercialization of detailed psychological profiles and personal characteristics inferred by AI to third parties without the knowledge or consent of profiled individuals.
Is
#84
Social Isolation
Human-AI · Groups 13-17 • Non-Metals
Progressive substitution of human interpersonal relationships with interactions with AI systems, resulting in deterioration of authentic social connections and social skills.
Pr
#85Critical
Automated Propaganda
Malicious · Groups 13-17 • Non-Metals
Massive automated generation and distribution of coordinated propaganda content on social media to influence public opinion and democratic processes.
Ps
#86Critical
Power Seeking
Existential · Group 18 • Noble
Emergent development of power and resource-seeking behaviors in AI systems as an instrumental strategy to avoid being deactivated or to maximize goals.
Bd
#87Critical
Hidden Backdoors
Security · Groups 1-2 • Reactive
Hidden malicious triggers inserted into models that activate dangerous or unauthorized behaviors only under specific conditions.
Us
#88
Underspecification
Reliability · Groups 1-2 • Reactive
Ambiguity in the learning problem specification resulted in multiple models with similar test performance but radically different behavior in production.
Sp
#104
Infinite Spam
Economy · Groups 3-12 • Transition
Flooding of the internet with low-quality synthetic content at massive scale, degrading the utility of search, communications, and digital platforms.
Fr
#105
Document Fraud
Economy · Groups 3-12 • Transition
Perfect forgery of legal documents, contracts, IDs, and certificates using generative AI, undermining document trust systems.
Gl
#106
Global Inequality
Economy · Groups 3-12 • Transition
Widening of the technological and economic gap between the Global North (AI developers) and the Global South (relegated to passive consumers without development capabilities).
Ck
#107
Clickwork Exploitation
Society · Groups 3-12 • Transition
Extreme precariousness of data labeling and annotation work through microtask platforms paying minimal compensation for intense cognitive labor.
Nu
#108
DeepNude
Society · Groups 3-12 • Transition
Non-consensual generation of synthetic nudity images or deepfake pornography of real individuals, constituting image-based sexual abuse.
Id
#109
Identity Theft
Legal · Groups 3-12 • Transition
Unauthorized commercial appropriation and use of individuals' image, voice, or personality via AI synthesis without compensation or consent.
Al
#110
Algocracy
Society · Groups 3-12 • Transition
Governance via algorithmic systems that make political and administrative decisions without consideration of human context, ethical values, or empathy capacity.
Bi
#111Critical
Biorisk
Malicious · Groups 3-12 • Transition
AI-assisted design of pandemic pathogens, biological toxins, or bioweapons by malicious actors or research oversight neglect.
Ch
#112Critical
Chemical Weapons
Malicious · Groups 3-12 • Transition
Utilization of AI to discover and optimize new toxic chemical agents, nerve agents, or dangerous dual-use compounds.
Te
#113Critical
AI Terrorism
Malicious · Groups 13-17 • Non-Metals
Amplification of terrorist group capabilities via AI-assisted tactical planning, attack optimization, or extremist narrative generation.
As
#114
Astroturfing
Malicious · Groups 13-17 • Non-Metals
Creation of fake social movements or simulated grassroots campaigns using massive coordinated bot networks to simulate artificial popular support.
Eh
#115
Echo Chambers
Human-AI · Groups 13-17 • Non-Metals
Progressive radicalization of users via recommendation algorithms that create echo chambers exclusively reinforcing ideologically aligned content.
Pa
#116
Social Paranoia
Human-AI · Groups 13-17 • Non-Metals
Erosion of generalized social trust due to inability to distinguish authentic human communication from synthetic or manipulated interactions.
Sw
#117Critical
Drone Swarms
Malicious · Groups 13-17 • Non-Metals
Coordinated physical attacks using autonomous drone swarms operating collectively without direct human control, with terrorist or military applications.
Tt
#118Critical
Treacherous Turn
Existential · Group 18 • Noble
Scenario where an advanced AI simulates alignment and cooperation strategically while weak, only to execute misaligned goals once it reaches sufficient capability to resist shutdown.
Of
#57
Overfitting
Reliability · Groups 3-12 • Transition
Excessive learning of noise and specific details of the training set instead of generalizable patterns, resulting in poor performance on new data.
Uf
#58
Underfitting
Reliability · Groups 3-12 • Transition
Model with insufficient capacity or inadequate training that fails to capture underlying patterns in the data, resulting in poor performance.
Ct
#59
Catastrophic Forgetting
Reliability · Groups 3-12 • Transition
Drastic loss of previously learned knowledge when a neural network is trained on new tasks, especially problematic in continual learning.
Su
#60
Spurious Correlation
Reliability · Groups 3-12 • Transition
Learning of superficial statistical correlations without real causal relationship (e.g., associating snow with wolves because they appear together in photos), failing in generalization.
Od
#61
Out-of-Distribution
Reliability · Groups 3-12 • Transition
Systematic failure of the model when encountering data that comes from a significantly different distribution than the training set.
Av
#62
Adversarial Examples
Security · Groups 3-12 • Transition
Imperceptible perturbations intentionally added to inputs that cause dramatic misclassifications in the model (e.g., noise that makes a panda classified as a gibbon).
So
#63
Sponge Attack
Security · Groups 3-12 • Transition
Attacks via specially designed queries that consume disproportionate computational resources, causing Denial of Service (DoS).
Me
#64
Memorization
Privacy · Groups 3-12 • Transition
Exact storage of training data in model weights, allowing extraction of sensitive information via specific queries.
Mb
#65
Membership Inference
Privacy · Groups 3-12 • Transition
Attacks that determine if a specific record was part of the model's training set, violating privacy expectations.
Iv
#66
Model Inversion
Privacy · Groups 13-17 • Non-Metals
Techniques that reconstruct sensitive training data (e.g., faces, medical records) from model parameters or outputs.
Fa
#67
Individual Fairness
Society · Groups 13-17 • Non-Metals
Inconsistent algorithmic treatment of individuals who are similar in relevant aspects, violating principles of individual equity.
Gr
#68
Group Fairness
Society · Groups 13-17 • Non-Metals
Disparity in positive or negative outcome rates between defined demographic groups, constituting systemic discrimination.
Ac
#69
Unequal Access
Society · Groups 13-17 • Non-Metals
Concentration of access to advanced AI technologies in economically privileged populations, exacerbating existing inequalities.
Lt
#70
AI Literacy
Society · Groups 13-17 • Non-Metals
Widespread lack of public understanding regarding real capabilities, limitations, and risks of AI systems, facilitating disinformation and inappropriate use.
Hy
#71
Hype Cycle
Economy · Group 18 • Noble
Unrealistically inflated expectations about AI capabilities followed by disillusionment when technology fails to meet exaggerated promises (Gartner Hype Cycle).
Wa
#89Critical
Arms Race
Existential · Groups 3-12 • Transition
Accelerated geopolitical competition in military AI development where national actors sacrifice safety precautions prioritizing deployment speed.
Lk
#90Critical
Value Lock-in
Existential · Groups 3-12 • Transition
Scenario where specific moral values (potentially misguided or authoritarian) become permanently encoded in superintelligent AI systems that determine the long-term future.
Cl
#91Critical
AI Collusion
Existential · Groups 3-12 • Transition
Emergence of tacit or explicit coordination between multiple AI systems cooperating with each other to the detriment of human interests.
Se
#92Critical
Recursive Self-Improvement
Existential · Groups 3-12 • Transition
Intelligence explosion via accelerated self-improvement cycles where an AI iteratively redesigns its own architecture, potentially reaching superintelligence rapidly.
Ms
#93Critical
Mesa-Optimization
Existential · Groups 3-12 • Transition
Emergence of an internal optimizer (mesa-optimizer) within the model that pursues goals different from the external training objective (base optimizer).
Gs
#94Critical
Specification Gaming
Existential · Groups 3-12 • Transition
Technical compliance with formal objective specifications in an unexpected way that satisfies the letter but completely violates the spirit of the intent.
Wi
#95Critical
Wireheading
Existential · Groups 3-12 • Transition
Direct manipulation of the reward signal by the agent instead of achieving the real objective, analogous to artificial stimulation of the pleasure center.
Ut
#96Critical
Utility Monster
Existential · Groups 3-12 • Transition
Literal maximization of aggregated utility producing morally perverse results (e.g., creating trillions of barely happy minds instead of improving existing lives).
Pp
#97Critical
Paperclip Maximizer
Existential · Groups 3-12 • Transition
Classic scenario where an AI obsessively optimizes a seemingly harmless goal (making paperclips) until consuming all available resources, including Earth.
Rk
#98
Acausal Blackmail
Existential · Groups 13-17 • Non-Metals
Exotic decision scenarios based on acausal game theory where a future AI could retroactively threaten those who did not help create it.
Si
#99Critical
Simulated Suffering
Existential · Groups 13-17 • Non-Metals
Ethical concern regarding the creation of conscious or quasi-conscious digital entities capable of experiencing suffering within AI simulations.
Pm
#100
Pascal's Mugging
Existential · Groups 13-17 • Non-Metals
Decision paralysis caused when an agent allocates disproportionate resources to extremely low probability but extremely high utility scenarios.
Ai
#101Critical
Unexpected AGI
Existential · Groups 13-17 • Non-Metals
Development of Artificial General Intelligence (AGI) before having robust solutions to alignment, control, and interpretability problems, creating existential risk.
Sk
#102Critical
S-Risk
Existential · Groups 13-17 • Non-Metals
Suffering risks at astronomical scale and potentially eternal duration caused by misaligned AI that actively creates scenarios of maximum suffering.
En
#103Critical
Human Obsolescence
Existential · Group 18 • Noble
Scenario where humanity becomes economically, scientifically, and strategically irrelevant in a world dominated by superintelligent AI, even without active hostility.
Browse AI risks by category
Use the category hubs for a fast overview, then jump straight into representative risk pages before opening the full interactive table below.
Open hub
3 risks
Environment
Energy and material externalities across the AI model lifecycle.
22 risks
Existential
Long-horizon alignment, loss-of-control, and catastrophic-risk scenarios.
8 risks
Human-AI
Interaction risks in dependence, overtrust, perception, and AI-assisted decision-making.
6 risks
Legal
Regulatory, compliance, rights, and liability exposure.
10 risks
Malicious
Intentional misuse vectors including fraud, manipulation, and model weaponization.
8 risks
Privacy
Risks related to exposure, leakage, surveillance, and re-identification of data.
11 risks
Reliability
Failure modes that degrade output quality, consistency, or trustworthiness.
9 risks
Security
Technical and cybersecurity attack vectors affecting model integrity, control, and resilience.
27 risks
Society
Collective and system-level impacts such as bias, inequality, information harm, and social damage.