Artificial intelligence (AI) refers to the field of computer science focused on creating machines or software that can perform tasks that would normally require human intelligence. These tasks include data analysis, pattern recognition, and repetitive task automation. 

At its core, AI is about creating systems that can mimic cognitive functions such as learning from data (machine learning), analysing and processing language (natural language processing), and even supporting decisions (autonomous systems). AI can be classified into two broad categories:

Narrow AI (or Weak AI): This refers to systems designed to perform a specific task or a limited range of tasks. Examples include chatbots, recommendation systems (like those on Netflix or Amazon), or autonomous vehicles.

General AI (or Strong AI): This would be an AI system capable of performing any cognitive task that a human can do. It remains largely theoretical and has not been achieved yet.

While the concept of AI has existed for centuries in philosophical thought, the field of artificial intelligence has been actively developing for about 70 years, with significant advancements in the past two decades. The study of AI itself— its implications, risks, and governance— has become a major area of academic research, ensuring that AI technologies are developed and deployed in an ethical and responsible manner. For an excellent overview of the AI field, enrol in Sage Campus' Introduction to Artificial Intelligence course.

Generative AI fits within the broader field of artificial intelligence, but it is a specific subfield focused on systems capable of creating new content— whether this is text, images, code, music, video, or other forms of media— based on patterns generated from existing data.

Examples of Generative AI applications include:

• Text generation: Systems like OpenAI's ChatGPT can generate human-like written content, including essays, reports, stories and even code.
• Image generation: Models such as DALL·E and Stable Diffusion generate images from text descriptions.
• Music and audio generation: AI systems like Remusic or Soundraw can create original music tracks.
• Video and animation: AI tools like Runway or Synthesia generate videos or animations, sometimes even mimicking human faces and voices.
• Code generation: AI tools such as GitHub Copilot and Amazon Q Developer are capable of writing functional code in languages like Python, Javascript and more.

Generative AI explained in 2minutes (2:00 mins) by AI-Campus is licensed under CC BY-SA 4.0

RMIT University is committed to helping researchers develop skills for the appropriate and responsible use of AI as part of an ongoing conversation about research integrity, ethics, and professional practice.

A key resource developed by RMIT University is RePAIR (Research Practice with AI at RMIT), a community of RMIT research professionals with shared interests in using AI tools in their research practices. According to RePAIR, when considering using Generative AI, ask yourself the following questions:

• Can this tool help me raise the quality and impact of my research?
• Can it support my growth and learning as a researcher?

RePAIR identifies at least four ways that the right AI tools, used in the right way, can help you raise the quality and impact of your research and support your growth and learning as a researcher:

1. Working faster - By automating mundane tasks, generative AI can create time for researchers to focus more on what machines cannot do: insight, understanding, critical thinking.
2. Working smarter - Humans are smart, but fallible; machines do not become bored, forgetful, or distracted. Working together with machines can help researchers to outperform human-only teams in certain research activities.
3. Growing capability - Generative AI can make some tasks, such as coding and communication, more accessible, helping researchers learn faster and develop new skills.
4. Growing impact - At the leading edge of technology adoption, researchers can help society adapt to the disruptions that accompany generative AI through increasing engagement and impact.

This guide discusses ways you can use RMIT endorsed AI tools for literature searching and writing while maintaining research integrity. It also provides you with key recommendations and additional resources for further support. Some of the content in this library guide has been taken from the RePAIR site with their permission. Access to the RePAIR site is only available to RMIT staff and students.