Will Teachers Be Needed In The Future

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Will Teachers Be Needed In The Future – The first blog post discussed how artificial intelligence (AI) will lead to educational technology products with freer agency. This post adds another dimension, that AI will allow students and teachers to interact with computers in a more natural way. Individuals will struggle to make choices that balance the attractiveness of natural interactions with potential risks.

In classic educational technology platforms, the ways in which teachers and students interact with computers are limited. Teachers and students can select items from a menu or a multiple-choice question. They can write short answers. They can drag objects on the screen or use touch gestures. The computer provides output to students and teachers through text, graphics and multimedia. Although these forms of input and output are versatile, there is no doubt about this style of interaction for how two people interact with each other; it is specific to human-computer interaction. With AI, interactions with computers tend to resemble human-to-human interactions (see Figure 1). A teacher can talk to an AI assistant and it can talk back. A student can create a drawing and the computer can highlight part of the drawing. A teacher or student can start writing something, and the computer can finish the sentence – like when today’s e-mail programs can finish our thoughts faster than we can type them.

Will Teachers Be Needed In The Future

Will Teachers Be Needed In The Future

In addition, the possibilities for automated actions that AI tools can perform are expanded. Current personalization tools can automatically adjust the order, pace, cues or path through learning experiences. Future actions might look like an automated agent helping a student with homework, or a teacher assistant reducing a teacher’s workload (recommending schedules that adapt to a teacher’s needs and are similar to schedules a teacher enjoyed before). Furthermore, an AI agent can appear as an additional “partner” in a small group of students working together on a collaborative task. An AI agent can also help teachers with complex classroom tasks, such as regulating the movement of students from a whole-class discussion to small groups and ensuring that each group has the materials needed to begin work.

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These new forms of interaction are likely to be attractive, but they also bring new risks that require our attention.

Early in the history of AI, Professor Joseph Weizenbaum of the Massachusetts Institute of Technology observed that when a computing device detects associations and automates actions, people interacting with the device describe it as “human-like” or “intelligent”—hence “artificial intelligence.” For example, a program from 1960 called “ELIZA” imitated a psychotherapist by detecting simple patterns in what people said and taking the next step.1 The person might say, “I have problems with my daughter” and the computer might write back, “Tell me more about your daughter .” In this example, ELIZA did not understand what the person said. ELIZA simply searched for a noun (“son”) and plugged nouns into a template response (“Tell me more about ____”. ) It may appear “intelligent” or “human-like” although the underlying process is not the same as how people understand language. Although ELIZA is not a “real” therapist, some treat the program as if it is one. the person needs personal and professional attention from a therapist, this can be very problematic.

The overestimation of what the computer can do becomes clearer as the form of interaction resembles more human interaction. When people associate computer intelligence, they may be more willing to accept recommendations that are not particularly intelligent or well-tested.

As computers interact in new ways with teachers and students, they also collect new forms of data. Collecting a student’s voice or likeness (either in a video or photo) is different from collecting their answer to a multiple-choice question. These forms of data contain more personal information than was collected by older forms of educational technology, which may create identity and privacy risks.

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On the automation side, there are also risks. Computers can generate a story that is novel and caters to a learner’s interests. However, the same technology can make it easier to automatically change information in ways that disrupt the learning process. The same problems with falsification of images that appear as “deep forgeries”2 in public life can arise in classrooms. While technology makes it easier to offer different learning activities to students in the same classroom, the sense of shared community in a classroom can be eroded. Without human oversight, AI systems can facilitate changing what students see or do in ways that introduce unwanted levels of controversy into teaching and learning environments.

When we visualize AI as an agent, it implies that we want to know when we are using AI (because we know when we are interacting with an agent). But this may not be the case. AI may not be immediately visible or obvious in certain teaching and learning applications—for example, when AI affects what happens next in a lesson or even what the lesson looks like. Even interactions that seem surprising at first can become second nature, and then go unnoticed. The risk will increase because more natural interactions are likely to be less dangerous to humans than the older style of human-computer interaction.

Parents and teachers should have the confidence to make informed decisions about future products they use for teaching and learning. However, it is important to recognize that evaluating AI systems in school technologies will be complicated. It will be difficult for individuals to make their own decisions. Today, people too easily give up personal data (eg on their phones, sign terms of use without reading them) to access convenient and interactive features. In schools, natural interactions enabled by AI systems will become more attractive – it will be difficult for decision makers to decide how to balance desirable new features with accompanying risks. Students in math class may prefer to share their handwriting rather than writing math in a difficult computer syntax. Communicating by voice with a classroom assistant can be so convenient for teachers that they decide to let the devices listen in their classrooms. The ability to answer an assignment without writing and by submitting a voice or video recording can be very beneficial for students. Because of this, trying to solve these problems by banning AI systems is unlikely to work. It is also dangerous to leave it up to individual teachers, parents and carers to make choices – it can be difficult for individuals to gather enough information to make an adequate decision. Instead, there is a clear federal role to support constituents of educational technology ecosystems in creating common policies that provide a clear foundation for sound educational decision-making.

Will Teachers Be Needed In The Future

1 Weizenbaum, J. (1966). ELIZA- A computer program for learning natural language communication between humans and machines.

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