Strengths and limitations of GenAI

What are the strengths of Gen AI?

It is clear that GenAI tools have the ability to imprint a very positive and meaningful array of use cases. Impact of tools will fluctuate on an individual level, however, in general, these tools have the ability to help learners with many aspects of their educational and professional careers.

Broadly, GenAI tools can readily be applied to support:

  • Personalised Learning Experiences
  • Increased productivity, and
  • Rapid creation of multimedia objects

Examples of these in practice include:

Developing personalised learning experiences based on pre-defined course material. Tools can adapt content in real-time and quiz students on key concepts, while analysing there understanding of the content and offering suggestions for revision.

Productivity can be increased by off-loading low-level tasks to the tool. For example, asking the tool to generate a suggested outline of a paper, or to summarise lengthy text. By using the correct prompts, some tools can generate ideas or plans to help kick start projects. These ideas can be refined and redeveloped rapidly. This can then allow students to progress with the deeper and more complex tasks that are required by the course.

Multimedia creation is now only limited by the prompt given to the tool. Students can now create digital assets to include in presentations to help strengthen key messages.

What are the limitations of GenAI?

Current AI tools have limits in terms of their ability to create meaning in the real world. The nature of these systems means that they do not understand the words that are being produced. For this reason, a human needs to evaluate the output from an AI tool much in the same way they must critically evaluate other media such as research papers and websites. In this way GenAI can provide opportunities for students to build critical analysis and evaluation skills, however, it is not a substitute for refined writing, critical thinking and evaluations skills. By studying and critiquing outputs from AI tools, students will gain better insights into their power and limitations.

Although much of GenAI focus lands on text generation, image and video GenAI tools have the ability to create realistic and professional outputs from a short prompt. These tools should also be considered in the same manner as text generated output, for example, if your assessment requires this material. Some key limitations are as follows:

  • Whilst output can appear plausible and well written, AI tools frequently get things wrong and cannot be relied upon for factual accuracy. 
  • They perform better in topics which are widely written about, and less well in niche or specialist areas. 
  • Unlike a normal internet search, some AI tools cannot access current websites and therefore, may produce out-of-date responses.
  • Some AI tools do not consistently provide (correct) references, sometimes fabricating these (NB: some AI tools can create references e.g., Perplexity). 
  • They can reflect and perpetuate stereotypes, biases, and Western perspectives, owing to the type and provenance of the data they have been fed, compounding the problem noted above about reliance of mainstream perspectives.
  • Their use has a high energy consumption e.g., one ChatGPT search uses more energy than one Google search.
  • The process by which these tools are built can present ethical issues. For example, some developers have outsourced data labelling to low-wage workers operating in poor conditions.

The creators of ChatGPT have provided the following guidance for educators and students which gives more guidance on capabilities and limitations than is provided here.