International Conference on Artificial Intelligence: Challenges, Issues & Impacts on January 14-16, 2027 in Istanbul, Turkey

Topics

Full Articles/ Reviews/ Shorts Papers/ Abstracts are welcomed in the following research fields:

1. Technical & Operational Challenges

These are the fundamental computer science and engineering hurdles inherent in building and deploying modern AI systems.

Data Scarcity, Quality, and Poisoning

The "Data Wall" (running out of high-quality human text for training)

Synthesized data loops (AI training on AI-generated content leading to model collapse)

Data poisoning and adversarial vulnerabilities (malicious actors corrupting training data)

The Black Box Problem & Lack of Interpretability

Explainable AI (XAI) deficiencies in deep learning

Difficulty tracing the decision-making logic of neural networks

Auditability challenges in safety-critical deployments (medicine, aviation)

Scalability, Energy, and Compute Costs

Hardware bottlenecks and the reliance on specialized silicon (GPUs/TPUs)

Carbon footprint and environmental impact of training massive foundation models

The democratization gap (only ultra-wealthy corporations affording state-of-the-art training)

Hallucination, Brittleness, and Alignment

The Alignment Problem (ensuring AI objectives match human values and intent)

Fabrication of facts (hallucinations) in Large Language Models (LLMs)

Brittleness in edge cases (systems failing when encountering data outside their training distribution)

2. Ethical & Moral Issues

These issues deal with the rights, values, and philosophical considerations raised by the behavior and deployment of AI.

Algorithmic Bias and Discrimination

Historical biases embedded within training data

Amplification of racial, gender, and socioeconomic prejudices in hiring, lending, and policing

The illusion of objectivity (treating biased machine output as absolute truth)

Privacy, Surveillance, and Consent

Mass data scraping without explicit creator or user consent

Biometric surveillance and facial recognition in public spaces

Inference tracking (AI predicting sensitive personal attributes like health status or political views from benign data)

Intellectual Property and Copyright Violations

Fair use doctrine versus copyright infringement in AI training sets

Ownership rights of AI-generated art, code, and literature

The economic displacement of human creators via data assimilation

Autonomy, Agency, and Deception

Dark patterns and algorithmic manipulation of human behavior (addictive loops)

Anthropomorphism (humans forming unhealthy emotional attachments to AI agents)

The ethics of artificial consciousness and the future definition of digital moral personhood

3. Societal & Economic Impacts

These topics explore how AI alters the fabric of daily life, industries, economies, and human interaction.

Labor Displacement and the Future of Work

Automation of cognitive and white-collar jobs (legal, writing, coding, administrative)

The widening productivity gap between AI-augmented workers and non-users

Economic inequality and the potential necessity of policies like Universal Basic Income (UBI)

Information Integrity and Democratic Erosion

The proliferation of hyper-realistic Deepfakes (audio, video, text)

Automated disinformation campaigns at scale targeting elections

The death of shared reality (epistemic fragmentation where citizens cannot agree on basic facts)

Psychological and Cultural Shifts

Cognitive atrophy (outsourcing critical thinking, writing, and problem-solving to machines)

Erosion of human-to-human social connection due to AI companionship

Homogenization of culture (AI models spitting out averaged, unoriginal creative outputs)

4. Geopolitical, Legal, and Regulatory Interrelations

This is where the previous three categories collide, forcing governments and global bodies to respond.

The Global AI Race and Sovereign Security

AI nationalism and export controls on semiconductor technology

Military applications (lethal autonomous weapons systems and AI-driven cyberwarfare)

The divide between nations controlling AI technology and nations merely consumed by it

Regulatory Frameworks and Enforcement

The fragmentation of global AI laws (e.g., risk-based compliance vs. market-driven innovation)

The pacing problem (technology evolving faster than legislative processes can draft laws)

The challenge of enforcing compliance across borderless, open-source AI ecosystems

Liability and Accountability

The legal blame game (who is responsible when an autonomous vehicle crashes or an AI misdiagnoses a patient?)

Corporate monopoly power and the concentration of systemic risk in a handful of tech giants

5. Frontier Risks

Speculative but highly researched topics regarding the ultimate trajectory of advanced intelligence.

Artificial General Intelligence (AGI) Timeline

Defining the thresholds of human-level adaptability across all cognitive tasks

The transition from narrow AI to generalized agents

Loss of Control and Superintelligence

The recursive self-improvement loop (Intelligence Explosion)

Existential risk (x-risk) and scenarios where humanity loses the ability to shut down or steer superintelligent systems

Name: IAAES
Website: http://iaaes.org