Next Gen AI Safety 2024 @ ICML Vienna

What does the next frontier in AI safety look like? How do we evaluate it? And how can we develop strong safeguards for tomorrow's AI systems?

Combatting the novel challenges of next generation AI systems necessitates new safety techniques, spanning areas such as synthetic data generation and utilization, content moderation, and model training methodologies. The proliferation of open-source and personalized models tailored for various applications widens the scope of deployments, and amplifies the already-urgent need for robust safety tools. Moreover, this diverse range of potential deployments entails complex trade-offs between safety objectives and operational efficiency. Taken together, there is a broad set of urgent and unique research challenges and opportunities to ensure the safety of tomorrow's AI systems.

In this workshop, we take a proactive approach to safety and focus on five emerging trends in AI and explore the challenges associated with deploying these technologies safely:

Agentic AI: As AI agents become more autonomous, concerns about unintended consequences, ethical issues, and adversary exploitation emerge. How do we ensure these agents respect privacy, and adhere to safety protocols?
Multimodal: With the evolution of AI systems to process and generate diverse modalities like audio, video, and images, concerns around content appropriateness, privacy, bias, and misinformation arise. How do we craft robust guidelines and security measures to tackle these challenges?
Personalized Interactions: As conversational agents evolve for social and personal interaction, risks like data privacy breaches and echo chambers grow. How do we balance tailored experiences with user safety?
Sensitive Applications: With AI's integration into high-risk domains like legal, medical, and mental health, the stakes rise with risks such as overreliance on automation and potential catastrophic errors. How do we ensure that AI systems in these critical areas enhance decision-making without compromising human expertise and judgment?
Dangerous Capabilities: As AI's knowledge and understanding capabilities improve, these systems could be leveraged to extract or generate information about harmful applications or technologies, including bioweapons or cyber attack methods. How do we ensure that AI systems are designed with safeguards to prevent their misuse in creating or disseminating dangerous knowledge, while still allowing for beneficial research and innovation?

We will bring together researchers across academia and industry working on improving safety and alignment of state-of-the-art AI systems as they are deployed. We aim for the event to facilitate sharing of challenges, best practices, new research ideas, data, and evaluations, that both practically aid development and spur progress in this area.

Call for Papers

Submissions open May 22nd! Read the full Call for Papers here.

Submission Instructions

To submit a paper, please follow the following instructions and policies.
- NGAIS is non-archival, but accepted papers will be made public via OpenReview.
- NGAIS is primarily an in-person event, and authors should be prepared to present a poster at the workshop.
- Submissions can be in-review or published at prior venues, but we will prioritize new submissions for presentation at the workshop.
- Papers should be up to 5 pages (excluding references and supplementary materials) in ICML 2024 format. Authors should anonymize their submissions, as our reviewing process is blinded.
- Authors should nominate at least one person to review submissions, with a reviewing load of at most 3 papers.
When ready, submit to OpenReview (opens May 22nd).

Important Dates

May 22: Submission portal opens

May 30 (AoE): Deadline for papers

June 17: Decision notifications

July 8 (AoE): Camera-ready deadline

July 26: Workshop!