What is Artificial Intelligence, or AI?
Artificial intelligence is the discipline within computer science to create machines that are able to learn and replicate tasks and processes that traditionally require human intelligence. Though the idea of AI has been around for many years, its academic study gained traction during a 1956 conference at Dartmouth University, where computer and cognitive scientist John McCarthy formalized the term “artificial intelligence.”
What are some important terms when studying artificial intelligence?
Machine learning is a subfield of artificial intelligence that involves the creation of algorithms that allows machines to draw upon data and past experiences to recognize patterns and make predictions either autonomously or with little human intervention.
Learned Language Models (LLMs) are examples of machine learning models that analyze large amounts of data and are able to understand human language and are then able to generate text in response to a prompt. ChatGPT is one of the more famous AI applications that uses LLMs.
What is Generative AI?
Generative AI is a form of artificial intelligence that can create content such as text, imagery, and even audio and. When prompted with questions or certain types of information, generative AI tools draw on massive datasets in order to provide a response.
What are some examples of Generative AI tools and chatbots?
Some of the more popular Generative AI tools in use right now are ChatGPT, Google Gemini, Claude, and Microsoft Copilot. These applications are still in the early stages of development, though improvements in artificial intelligence have advanced rapidly as more investment and research have gone into its various use cases.
What fields currently use artificial intelligence?
Most areas of society currently use artificial intelligence to analyze data rapidly and improve efficiency. Healthcare, finance, and even law are some of the fields that are predicted to face increased disruption due to the growth of AI. In higher education, both students and instructors are beginning to explore the positives and negatives of using AI in the classroom.
Increases the efficiency of certain tasks: AI is able to automate tasks that are often considered monotonous. Even its current early state, it can complete tasks such as data entry and the generation of documents such as lesson plans and outlines quickly. AI also eliminates the variable of human error when performing this function. Ultimately, this frees up the time of both students and employees in higher education.
Handles large amounts of data: AI is able to analyze and draw conclusions from huge data sets in a very short amount of time, something people simply cannot do with the same combination of speed and accuracy. By using algorithms and machine learning, AI can use this data to make quick and efficient decisions. AI is also available to analyze data and provide responses 24/7, thus making it readily available whenever needed.
Personalizing the student experience: Students can currently use AI to help them get started on certain projects that may seem intimidating; rather than label it as cheating, getting ideas from AI services such as ChatGPT can unlock research pathways that may have not seemed obvious before. AI can also be used by educators to quickly analyze student data to better help them create a learning experience that benefits a larger number of individual students. AI is also becoming increasingly more accurate in translating material from one language to another, which can aid individual students in better understanding their assignments.
Results generated can be unreliable: There have been cases where AI generate what has been termed 'hallucinations.' This is often do to limited datasets that AI tools have access to and improper training of the AI. One area where this has been most prominent is in the creation of citation information, where the AI generates citations or entire articles that don't actually exist. There have also been cases where AI has generated insufficient or inaccurate results when prompted with certain inquiries, which shows the importance of users learning how to prompt AI in a way that brings the best results.
Concerns over cheating and the erosion of critical thinking skills: Many educators have expressed concern that AI will be used by their students to cheat on assignments, although tools that help them detect the use of services such as ChatGPT are improving. There is also the possibility that reliance on AI will affect students' opportunities to learn critical learning skills over time, and will ultimately damage their ability to produce original or creative thought on their own.
Reinforcement of existing bias: A current worry in the early stages of AI tools is that they will generate results that reinforce existing bias that exist in our society due to their prevalence in the data AI is trained with. Experts feel this could lead to a number of harmful results. Groups such as women and minorities can potentially be underrepresented in existing datasets, leading to issues with accuracy and implicit bias. It can also lead to the failure of AI tools to predict and detect new patterns that are important in their use cases.
Generative AI tools are trained using data gathered from various sources, including web scraping and user-provided inputs such as text or images. Some tools have been trained using content scraped from websites without the consent of the site owners. Additionally, inputting copyrighted material into these tools may contribute to their training and subsequent responses to other users.
Ongoing legal cases argue that using artists' or writers' content to train generative AI constitutes copyright infringement. The courts must determine whether this use qualifies as fair use or infringement.
Regarding the ethical question:
Is the use of generative AI tools a violation of copyright? Copyright protects the intellectual property of human creators. To navigate this issue: