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John S. Erickson

John Erickson
Director of Research Operations, Director of Web Science Operations
Email: erickj4@rpi.edu
Homepage: https://idea.rpi.edu/people/staff/john-s-erickson
Blog: http://bitwacker.com
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John S. Erickson, Ph.D. has spent over two decades studying the unique social, legal, and technical problems that arise when managing and disseminating information in the digital environment. Currently Director of Research Operations at the Rensselaer Institute for Data Exploration and Application (IDEA) and Deputy Director of the Web Science Research Center of the Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI), John coordinates, contributes, and teaches. Prior to joining RPI John was principal investigator on research at Hewlett-Packard Labs focusing on policy-based management and personalization of distributed, heterogeneous digital object repositories, content processing architectures and collaboration systems. Before joining HP John was an entrepreneur, having created the first Web-based service to fully automate the complex copyright permissions process for a variety of media types, and the first digital rights management (DRM) technology to facilitate dialog and metadata exchange between content creators and users.

 

 


Affiliations: Tetherless World Constellation, Rensselaer Polytechnic Institute, The Rensselaer Institute for Data Exploration and Applications

Projects as Research Staff

Technical and Legal Aspects of Regulating Generative AI

Large generative AI models (LGAIMs), such as ChatGPT, GPT-4 or Stable Diffusion, are rapidly transforming the way we communicate, illustrate, and create.

ChatBS: A Context-aware LLM Exploratory Sandbox

ChatBS: A Context-aware LLM Exploratory Sandbox uses the OpenAI Completion API service (GPT-4-0613 model) to answer questions.

Health Empowerment by Analytics, Learning, and Semantics (HEALS)

The Center for Health Empowerment by Analytics, Learning, and Semantics (HEALS) is a five-year collaboration between Rensselaer and IBM aimed at researching how the application of advanced cognitive computing capabilities can help people to understand and improve their own health conditions.

Semantic Data Dictionaries (SDD)

The aim of the Semantic Data Dictionary (SDD) approach is to annotate datasets such that it is machine readable, uses best practice ontologies, and follows FAIR Guiding Principles.

The Human-Aware Data Acquisition Infrastructure (HADatAc)

HADatAc (Human-Aware Data Acquisition framework) is an open-source infrastructure that enables combined acquisitions of data and metadata in a way that metadata is properly and logically connected to data.