This conference delves into the evolving field of algorithmic nudging, an advanced application of behavioral economics wherein AI-driven algorithms subtly guide decision-making in digital environments. Building on traditional nudge theory’s foundations, algorithmic nudges leverage personalization, real-time data, and machine learning to influence choices ethically and effectively at scale. The event focuses on the balance between behavioral influence and user autonomy, exploring the risks, benefits, and societal impacts of AI-powered choice architectures across sectors such as finance, health, and sustainability.
Structure and Sessions (Who Does What):
Organizing Committee: Develops the conference agenda, contracts speakers, and manages virtual event logistics.
Keynote Speakers: Thought leaders from behavioral economics, AI ethics, and digital policy provide foundational and forward-looking insights.
Presenters: Academics, AI developers, ethicists, and industry practitioners share research findings, case studies, and applications.
Participants: Engage with content through Q&A, panel discussions, and networking sessions.
Technical Review Committee: Reviews submitted abstracts and papers for relevance, quality, and contribution to the field.
Participate and Contribute (Who Benefits):
Behavioral Economists and Social Scientists: Gain advanced understanding of AI-enabled behavioral interventions.
AI and Data Scientists: Explore ethical design and efficacy metrics for algorithmic nudging systems.
Policy Makers and Regulators: Understand governance challenges and develop frameworks for responsible use.
Business Leaders and Marketers: Learn how to ethically apply nudging to enhance customer engagement with transparency.
Academics and Researchers: Present novel research and contribute to peer-reviewed indexed journals.
Benefits:
Certificate of Participation awarded based on feedback submission.
Commemorative momento recognizing participant contribution.
Abstracts and selected papers published in prestigious indexed journals such as Scopus, CrossRef, WoS, Elsevier, and SCI-indexed journals.
Abstract Topics / Call for Papers (CFP) Tracks:
Foundations and Evolution of Algorithmic Nudging
Ethical Principles in AI-Driven Choice Architecture
Personalization, Privacy, and User Autonomy in Nudging
Measuring Behavioral Change and Efficacy of Nudges
Algorithmic Transparency and Explainability
Applications in Finance, Health, and Sustainability Domains
Regulatory and Policy Considerations for Algorithmic Nudges
Psychological Impacts of AI Mediated Decision Environments
Designing for Equity and Avoiding Behavioral Bias Amplification
Future Directions: Integrating AI, Behavioral Science, and Ethics
Registration:
Online registration portal open for professionals, academics, and students.
Call for abstracts with clear submission guidelines and timelines.
Attendees receive full access to live sessions, recordings, conference materials, certification, and publication opportunities.
Detailed Program Grid (2 Half Days, 9 AM to 1 PM)
Time
Day 1
Day 2
09:00 – 09:15
Opening Ceremony & Conference Introduction
Recap of Day 1 & Opening Keynote
09:15 – 10:00
Keynote Session I: Algorithmic Nudging – Foundations and Innovations
Keynote Session III: Ethics and Transparency in AI Nudging
10:00 – 10:45
Technical Session I: Personalization and Behavioral Impact Measures
Technical Session III: Regulatory Challenges and Policy Frameworks
10:45 – 11:00
Q&A and Networking Break
Q&A and Networking Break
11:00 – 11:45
Technical Session II: AI in Finance and Health – Case Studies
Panel Discussion: Balancing Autonomy and Influence in AI-Driven Choice Environments
11:45 – 12:30
Abstract Presentations and Research Highlights
Technical Session IV: Designing Ethical and Effective Nudges
12:30 – 13:00
Participant Feedback and Interactive Dialogue
Closing Ceremony & Certificate Distribution
This conference offers deep insights into the intersection of behavioral economics and artificial intelligence, facilitating important discussions on the ethical design and practical impact of algorithmic nudging, coupled with certification and publication opportunities in leading academic outlets.
