Research Guides: AI Guide: AI Tools

AI Research Tools

Here is a list of current research tools that utilize AI functions to provide a more intuitive and productive experience for your research journey:

ASReview
An open-source systematic review assistant, freely available for use, employs cutting-edge active learning techniques to facilitate the examination of extensive article/content collections for targeted keywords and qualifiers. Initially created by researchers at Utrecht University, this software has evolved into a non-profit initiative led by a collaborative team of multidisciplinary researchers and system engineers nationwide.
Elicit
Summarizes articles, finds similar research articles, and extracts data from articles into easy to read tables. Offers base free access and then tiered subscription.
JSTOR- Generative AI
JSTOR, a nonprofit service from ITHAKA, invites you to explore the beta release of a new generative AI-powered research tool. The tool with summarize texts, help users identify key terms and other relevant information.
Library of Congress - Humans in the Loop
Library of Congress Labs have been studying machine learning for several years. They have developed a framework for assessing their machine learning tools to complete specific tasks. Find their documents for assessment linked here.
Research Rabbit
Research Rabbit, at researchrabbit.ai, visually manages and discovers research through an AI-driven literature mapping tool. Using a "seed" article, it forms a bubble map of connected topics, aiding in interdisciplinary connections and staying current. Developed by a collective committed to open access, it's free with sign-up.
SciSpace
SciSpace, a Scientific Collaboration Workspace, consolidates shared information from diverse HPC data centers, ensuring high-performance data access within native namespaces. It optimizes scientific collaborations across centers with a search and discovery service. Real datasets and applications demonstrate a 36% performance boost through native-data access.
Semantic Scholar
Leveraging publisher partnerships, data providers, and web crawls, this AI-powered search tool offers a streamlined platform for 200 million+ academic papers. Developed at the Allen Institute for AI since 2015, it aims to support high-quality research. Free to use.

AI Image Generation Tools

Here is a list of current software tools that utilize AI functions to generate images based on text prompts:

Adobe Firefly
Firefly is Adobe's generative AI image creator. Access it with your UHCL credentials.
Bing Image Creator
Image Creator from Designer helps you generate images based on your words with AI.
Dall-E
DALL-E software generates images from textual descriptions using advanced generative AI techniques.
Dreamstudio
Images generator based on text prompts.
Midjourney
Midjourney Image Generator software is a tool designed to create images using generative AI techniques during the early stage of a creative process.

AI Writing Assistant Tools

Here is a list of current software tools that utilize AI functions to assist in the writing process:

Gemini
Google's free AI solution
Microsoft Co-Pilot
Microsoft's AI tool that provides a variety of AI outputs, including text generation and image generation. Copilot uses a version of ChatGPT, but unlike ChatGPT, when logged in with your institution credentials, copilot does not add your input information into its knowledge base.
Sudowrite
Sudowrite is a subscription writing assistant software that can support idea generation and editing support.

The CLEAR Framework for AI Prompts

Many generative AI resources will require users to provide a prompt to start using the resource. Creating well defined prompts will get you better results when using AI. The CLEAR Framework, developed by Leo S. Lo, University of New Mexico, can be used in order to develop productive prompts.

Concise: Use brevity and clarity in prompts. Use concise and explicit language in your prompts.

Logical: Use structure and natural progression within your prompt to produce a more natural relationship between concepts.

Explicit: Include specifics about the type of information and amount of output you are requesting.

Adaptive: Experimenting with various prompt formation will help the user reach the output desired.

Reflective: Continue to evaluate and revise upon prompts for perpetually improvement.

Read more about the CLEAR framework by Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720–. https://doi.org/10.1016/j.acalib.2023.102720