Semantic Scholar

• Finds semantically similar research papers
• Covers over 220 million papers from all fields of science (many other AI tools are built from this platforms holdings & features)
• Pen icon reveals highlighted key points
• Offers a library folder where you can save results and research feeds will recommend similar papers based on the items saved in your folder.

Elicit

• Locate papers, filter by study types, automate research flow, brainstorming, summarize takeaways and identify themes
• Covers over 125 million papers

Consensus

• Distills scientific findings and extracts key results and insights
• Covers over 200 million scholarly documents and papers
• Focuses on all domains of science: medical, natural and social
• Consensus Meter examines a selection of studies and illustrate their collective agreement

OpenRead

• Over 300 million papers and real-time web content
• Paper Q&A feature allowing users to answer any questions about a paper
• Contains a trending topics section and offers a translation feature

Scite.AI

• Citation index displaying the context of citations and classifies their intent
  • how many times was it cited by others
  • how was it cited by others by displaying the text where the citation occurred from each citing paper
  • whether the citation offers supporting or contrasting evidence of the cited claims in the publication of interest
• 1.2 billion citation statements and metadata from over 181 million papers

Paper Digest

• Distills articles, conference papers, patents, grants, clinical trials, etc. into easy-to-read digests
• Literature Review (hallucination free)

Research Rabbit

• Citation-based literature mapping tool
• Millions of academic articles

Inciteful

• Consists of two tools
  • Paper Discovery builds a network of papers from citations to identify the most relevant literature
  • Literature Connector is intended to compare two sources and details how the literature connects them together
• Over 2 billion papers from journals and books

Litmaps

• Specializes in literature review mapping through engaging visuals recommending where to start and relevant related sources
• Over 270 million papers

Scholarcy

• Distills papers into summaries, highlighting key claims, data and visuals into a flashcard format to reduce information overload
• Offers a Research Quality Indicator to score a paper across a range of research indicators
• Literature Synthesis Matrix allows a user to export multiple flashcards to Excel to easily compare key findings, data, and other information points

This framework is used to evaluate the credibility and trustworthiness of information related to content generated by artificial intelligence (AI).  These questions are designed to encourage users to actively question the source and context of information generated by AI, rather than passively accepting it. 

Reliability:

How dependable and consistent is the information source regarding the AI technology?

• If the content is not produced by the party responsible for the AI, what are the author(s) credentials? Biases?
• If the content is produced by the party responsible for the AI, how much information are they making available?
  • Is information only partially available due to paywalls?
  • Is it current information?
  • Does the information actually exist or is it a work of fiction because the AI is hallucinating?

Objectivity:

Does the information present a neutral perspective without personal opinions or biases?

• What is the purpose or goal of the use of AI?
• Is there transparency with what types of information or datasets are being used with the AI?
• Is there any information or datasets being intentionally excluded from users?

Bias:

Are there any inherent prejudices or skewed viewpoints in the information presented about the AI?

• What ethical issues are associated with AI?
• Are ethical issues and biases acknowledged by the source? Its users? or by the party responsible for the AI?

Ownership:

Who developed or is responsible for the AI technology, and does this influence the information provided?

• Is the AI technology open to all or do barriers exist (inequity)?
• Who has access to it?
• Who can use it?
• Can the content or algorithms be changed or customized?

Type:

What kind of AI technology is being discussed (e.g., machine learning, natural language processing) and how does this impact its functionality?

• What kind of information system does it rely on?
• Does it rely on human intervention?

This framework is licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International License.

Hervieux, S. & Wheatley, A. (2020). The ROBOT test [Evaluation tool]. The LibrAIry. https://thelibrairy.wordpress.com/2020/03/11/the-robot-test.