Generative AI is a transformative technology with the potential to revolutionize workflows across Adelphi University. 

While faculty and students delve into the exciting possibilities and ethical considerations of generative AI through the AI Task Force, this technology also has great potential for administrative workflows. Generative AI offers significant advantages for staff, streamlining processes and freeing up valuable time for higher-level work.

Here are a few practical ways to leverage generative AI:

  • Enhanced Communication: AI can personalize emails, generate reports, and translate documents, streamlining staff communication with students, faculty, and external parties.
  • Idea Generation: Brainstorming new initiatives or solutions? Generative AI can suggest innovative approaches and content, sparking creative problem-solving.
  • Data Analysis and Automation: AI can analyze vast datasets, identify trends, and automate repetitive tasks like scheduling or data entry, freeing up staff time for higher-level work.

Microsoft Copilot for Education

Microsoft Copilot is an AI-powered chat assistant designed specifically for education and is available to Adelphi University faculty and staff who have Microsoft 365 accounts. It provides real-time answers to questions using the latest AI models like GPT-4 and DALL-E 3.

To begin using Copilot, access it at adoption.microsoft.com, or use the iOS/Android app. You can also find it in the Microsoft Edge sidebar and Windows 11. Dive in to unlock its full potential for your classroom.

Copilot provides commercial data protection:

  • User and organizational data are safeguarded.
  • Chat data is not saved.
  • Microsoft has no eyes-on access to it.
  • It is not used to train the underlying large language models.

Microsoft adheres to AI principles and Responsible AI Standards. Copilot’s design prioritizes privacy-preserving machine learning. Your data remains confidential, and Copilot doesn’t store chat data.

Explore the following resources:

Yes, consider using Copilot Studio to tailor Copilot to your specific needs within Microsoft 365.

Read the Microsoft Education Blog post to explore additional insights and use cases.

Google Gemini

The current version of Gemini, powered by the Gemini AI model, is a large language model capable of performing a wide range of tasks with high accuracy and fluency.

Research:

  • Find scholarly articles on a specific topic.
  • Summarize key points from an article or book.
  • Generate citations in different styles (APA, MLA, Chicago).

Writing:

  • Brainstorm ideas for essays, research papers, or presentations.
  • Paraphrase existing text to avoid plagiarism.
  • Improve the clarity, conciseness, and flow of your writing.

Learning:

  • Get answers to your course-related questions.
  • Explain difficult concepts in simpler terms.
  • Translate text and research materials from other languages.

While Gemini can be a valuable tool to improve your learning and writing, it is important to remember:

  1. Don’t plagiarize: Use Gemini’s output as a starting point for your own work, but always cite your sources properly.
  2. Develop critical thinking skills: Don’t rely solely on Gemini’s answers. Evaluate the information it provides and form your own conclusions.
  3. Focus on understanding: Use Gemini to clarify concepts, not just generate answers.

Find out more about plagiarism and Academic Integrity at Adelphi.

Gemini is currently in beta testing, but there are resources available to learn more about its capabilities. You can visit the Gemini web application or contact your university librarian for information about potential access.

Gemini is committed to protecting your privacy. It does not access your personal information or course materials.

If you have any questions about using Gemini, please contact your University Librarian or the IT Help Desk.

Data Classification Standards

Not sure what information should you put into generative AI? Here’s a quick explanation:

Restricted

Sensitive

Internal

Public

This category includes highly sensitive data that is tightly controlled due to legal, regulatory, or ethical considerations. Examples might include Protected Health Information (PHI), classified government documents, trade secrets, and confidential agreements.

It’s crucial to restrict access to this information and ensure it is not used in generative AI systems without proper authorization.

Sensitive data encompasses information that, if compromised, could cause harm to individuals or organizations. This includes personal data— de-identified or personally identifiable information (PII)—such as financial information, and health records.

Handling this data requires robust security measures to safeguard against unauthorized access or disclosure.

Internal data refers to information used exclusively within an organization for its operations or decision-making processes. This may include proprietary algorithms, employee records, and strategic plans.

Access to internal data should be restricted to authorized personnel, and its use in generative AI systems should be carefully controlled to prevent leaks or misuse.

Publicly available data is information that is freely accessible to anyone and does not require special authorization to view or use. This includes data from public websites, government reports, and publicly disclosed research findings.

It’s still important to exercise caution and ensure compliance with any applicable usage terms or copyrights when incorporating public information into generative AI systems.

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