5th MANILA International Conference on Artificial Intelligence: Challenges, Issues & Impacts (AICII-26)

Call for Papers

Full Articles, Reviews, Short Papers, and Abstracts are welcomed in the following research fields.

The field of Artificial Intelligence (AI): Challenges, Issues & Impacts is one of the most critical and fast-evolving areas of discussion across technology, ethics, law, and economics. The topics are organized into three core pillars:

1. Challenges in AI Development (Technical & Implementation)

Explainability and Interpretability (XAI):

• The "Black Box" problem: Making complex deep learning models understandable
• Methods for Explainable AI (XAI) to build user trust and enable auditing

Data and Robustness:

• Challenges in curating, securing, and standardizing the massive datasets required for training frontier models
• Data Privacy vs. Data Utility: Reconciling AI's need for data with privacy regulations (like GDPR)
• Adversarial Attacks and Security: Protecting AI systems from malicious input and data poisoning

Resource and Environmental Impacts:

• The massive computational cost (GPUs) and energy consumption required for training large models
• Environmental Footprint: Water consumption for cooling data centers and the contribution of AI infrastructure to e-waste and carbon emissions

Scalability and Integration:

• Difficulties in scaling AI initiatives from successful pilots to full enterprise implementation
• Challenges of integrating modern AI tools with legacy or outdated IT systems

2. Ethical Issues and Societal Bias (Bias & Fairness)

Bias and Discrimination:

• Algorithmic Bias: Identifying and mitigating bias embedded in training data that leads to discriminatory outcomes
• Impact of bias in critical sectors: Hiring/Recruitment, Credit Lending, Healthcare Diagnostics, and Criminal Justice

Accountability and Liability:

• Determining who is legally responsible when an autonomous AI system causes harm or makes an incorrect decision
• Defining the scope of human oversight and control over increasingly autonomous AI agents

Manipulation and Misinformation:

• The creation and dissemination of Deepfakes (audio, video, text) and their impact on democracy, politics, and trust
• AI's role in amplifying filter bubbles and polarizing public opinion through biased content recommendations

Creativity and Ownership (IP):

• Intellectual Property (IP) and Copyright challenges for content generated by AI models trained on existing copyrighted works
• Defining originality and ownership of AI-generated creative works

3. Economic and Human Impacts (The Transformation)

The Future of Work and Labor Economics:

• Job Displacement and Automation: Assessing the risk of automation across different sectors
• Workforce Transformation: The need for massive reskilling and upskilling programs
• Economic Inequality: Analyzing how AI-generated wealth and productivity gains are distributed

Governance and Regulation (Policy):

• Global AI Regulation: Comparing approaches (e.g., the EU AI Act, US executive orders) and seeking international alignment
• Risk-Based Regulation: Developing frameworks that adjust regulatory intensity based on the level of risk
• Digital Sovereignty: The role of nations and international bodies in establishing ethical guidelines

Impacts on Specific Sectors:

• AI in Public Health (e.g., personalized medicine, drug discovery) and the accompanying privacy risks
• AI in Education (e.g., personalized learning, automated grading) and its effect on the role of human educators
• The use of AI in Warfare and Security (e.g., autonomous weapons systems)