Q. I have a 2005 Buick Lacrosse and it has been making a clacking, snapping sound when I brake, and 50-100 ft after brake is released. The sound itself seems to come from the from the brake on the left side, and toward the center front in the car. Sometimes if I hit an unforeseen bump which cannot be avoided, I hear the same sound. The mechanic replaced the left front tie rod, but the noise remains.

A. I would start by going on a road test with a mechanic so you both hear the same noise. I suspect that the first repair was on the right track. It is possible something in the front suspension, inner tie-rod end wear is common, stabilizer links, body mounts or even a brake caliper is shifting could be making the noise.

Q. The speedometer is practicing way out of normal range (on the dial). Does the dash need to be removed to repair this, or does the speedometer mechanism have to be replaced entirely? Can it be reset?

A. This really depends on the age and type of vehicle. Nearly all speedometers today are electronic and do not use traditional cable drives. The issue could be the speed sensor in the transmission, or a faulty circuit in the instrument panel. A technician with a scan tool should be able to determine is the speed sensor is working properly.

Q. The steering wheel whirrs when I make a sharp right or left turn and the noise seems to be outside the car. Is this a simple repair job?

A. There could be several causes of this noise, from low power steering fluid to a worn or losoe power steering belt.

Q. I own a 2015 Mercedes GLK 250 diesel, which has displayed the check engine light frequently. The dealership has checked this out with repairs and claimed it to be part of the recall for diesel emissions. The recall was completed, and the light still returned intermittently. It frequently occurred after long road trips over 150 miles and with subsequent driving sometimes went off by itself. Mercedes high end repair shops recommended replacement of the entire sensor board since they said it was easier to affect a repair by its replacement rather than trying to replace the sensors individually. This is a very expensive repair. They said that since l am a Mercedes owner, I could afford the expense. Hogwash. Is this a Mercedes engineering fiasco?

A. The first thing that needs to be performed is a test to see what codes are causing the check-engine light. There are some common issues with this vehicle. Some or all of the following could cause a check engine light to be illuminated intermittently. There could be a vacuum leak, damaged and leaking O-rings, damaged water pump impeller, low battery voltage and even contaminated coolant or engine oil. Using the “parts-cannon or shotgun” approach of just throwing parts at the car almost never actually repairs the issue and is certainly not in the customer’s best interest.

Q. I have a 2006 Toyota Sienna, 103,000 miles, runs great, well maintained with no problems. Should I have the transmission fluid changed? As far as I know. The fluid was never changed.

A. Toyota considers it a lifetime fill and unless there is a leak or other issue is good for the lifetime of the car. But you could certainly change it as a preventative measure. If you do use only Toyota or equivalent fluid, not a generic fluid used in some flushing machines. If it were my vehicle and I drove it “normally” I would leave well enough alone.

Q. My Husband’s car was taken to get an oil change and inspection sticker yesterday. They did the oil change but rejected the car for the sticker. The reason was front body rot/rust. A front cross member piece is needed because it is so badly rusted. The car is a 2007 Chrysler Pacifica; do you think one could be found? He loves the car, and it still looks great. Any suggestions?

A. Yes, you can find a good rust free front subframe on eBay motors and other salvage yard websites. The part is $6-$900 plus about six hours labor to install it, plus a wheel alignment. There could be added expenses due to other rusty parts, but yes it can be repaired.

Q. I own a 2016 black Subaru Forester and I need to touch up some scratches. Can you please recommend a good brand to purchase for me to do the job myself?

A. The brand that I have been most happy with over the years is www.automotivetouchup.com Great color match and everything from touch up pens to quarts and gallons. Plus, they have clear coat paint to get the factory finish look. Recently I was alerted to another similar company https://touchuppaintfactory.com which also has factory color match in all size applicators. Like all painting, the preparation before painting is what determines the outcome of the job.

Q. I recently saw a Chevrolet at a car show, it was a small two-door wagon (not a Chevrolet Vega). The car was highly modified with a big V-8 engine. The steering wheel was on the left and I suspect it may have been a Canadian car. Is this enough of a clue to know what it could be?

A. What you may have seen (and I just saw one recently) was a Chevrolet Caravan. The car was from Brazil and sort of a combination of a Chevy and Opel. Sometimes referred to as an Opala, the factory engine was a 2.5-liter, 150 cubic-inch four-cylinder, but over the years many four-cylinder engine were replaced with a larger 250 cubic inch straight six-cylinder engine.

Got a car question, email the Car Doctor for a personal reply. jpaul@aaanortheast.com

ChatGPT's ability to provide conversational answers to any question at any time makes the chatbot a handy resource for your information needs. Despite the convenience, a new study finds that you may not want to use ChatGPT for software engineering prompts.  

Before the rise of AI chatbots, Stack Overflow was the go-to resource for programmers who needed advice for their projects, with a question-and-answer model similar to ChatGPT's. 

Also: How to block OpenAI's new AI-training web crawler from ingesting your data

However, with Stack Overflow, you have to wait for someone to answer your question while with ChatGPT, you don't. 

As a result, many software engineers and programmers have turned to ChatGPT with their questions. Since there was no data showing just how efficacious ChatGPT is in answering those types of prompts, a new Purdue University study investigated the dilemma. 

To find out just how efficient ChatGPT is in answering software engineering prompts, the researchers gave ChatGPT 517 Stack Overflow questions and examined the accuracy and quality of those answers. 

Also: How to use ChatGPT to write code

The results showed that out of the 512 questions, 259 (52%) of ChatGPT's answers were incorrect and only 248 (48%) were correct. Moreover, a whopping 77% of the answers were verbose. 

Despite the significant inaccuracy of the answers, the results did show that the answers were comprehensive 65% of the time and addressed all aspects of the question. 

To further analyze the quality of ChatGPT responses, the researchers asked 12 participants with different levels of programming expertise to provide their insights on the answers. 

Also: Stack Overflow uses AI to provide programmers new access to community knowledge

Although the participants preferred Stack Overflow's responses over ChatGPT's across various categories, as seen by the graph, the participants failed to correctly identify incorrect ChatGPT-generated answers 39.34% of the time.  

According to the study, the well-articulated responses ChatGPT outputs caused the users to overlook incorrect information in the answers. 

"Users overlook incorrect information in ChatGPT answers (39.34% of the time) due to the comprehensive, well-articulated, and humanoid insights in ChatGPT answers," the authors wrote. 

Also: How ChatGPT can rewrite and Improve your existing code

The generation of plausible-sounding answers that are incorrect is a significant issue across all chatbots because it enables the spread of misinformation. In addition to that risk, the low accuracy scores should be enough to make you reconsider using ChatGPT for these types of prompts. 

Q: Who is allowed to submit or enter final grades?

A: Final grades must be entered or submitted online via myPurdue Faculty Self Service or BrightSpace by the instructor of record for that course.

Q: How do you know that you're an instructor of record?

A: Log into myPurdue and look in the My Course channel from the Faculty tab. If you have access to course lists, you will see your course offerings. If all do not appear, select the more link under your visible courses.

Q: What if I make a mistake or need to change a student’s final grade after I have submitted it?

A: Grades can be resubmitted through myPurdue or BrightSpace as often as you need up to the deadline. Corrections after that will require a Form 350 or a change submitted using the Grade Change Workflow in myPurdue.

Q: I keep getting the same final grade roster when I click Final Grade entry.

A: Scroll to the bottom of your final grade page and look for the link called "CRN Selection". Click on it and a drop down for all the courses you are faculty of record will display. Click on the arrow for a full list. Select your next CRN, then hit Submit.

Q: When can students see grades in Banner/myPurdue?

A: Students will be able to view grades after they have been rolled to academic history. That process should be complete by 8:00 a.m. the morning after the grade entry deadline.

Q: Can grades be printed?

A: To print a copy of grades for your records, click on "download course roster" from your final grade page.

Q: How can grades be viewed after grades have been rolled to history?

A: Faculty may view their grade rosters again after the deadline has passed and all end of term processing has completed in myPurdue. This is typically by 8:00 a.m. the following day. Grade reports are available using Cognos – Public Folders-Validate-Grades through the schedule deputy in each department for faculty.

Q: What if I have a Pass or No-Pass class?

A: A grade of Pass (P) or No-Pass (N) may be used if the course was originally set up with that grading criteria. If you are assigning an incomplete grade for a Pass or No-Pass class, the grade of PI should be given. If you are pushing grades from BrightSpace, the letter grade you push will automatically convert to a P or N based on the rules in university regulations.

Q: How do I handle regular incomplete grades?

A: Incomplete grades are assigned when a student has attended class, but has not completed work and has been allowed time to do so. As before, a Registrar Form 60 must completed for each student with an Incomplete or (I) grade submitted..

Incompletes are not to be used for students who never attended class and are still on the class roster. Failure to complete the class or turn in passing coursework is noted as an (F).

Q: How do I know if I should assign an "F" grade or an "FN" grade?

A: A grade of F (Failing) is awarded to students who complete the course and participate in activities through the end of the term but fail to achieve the course objectives. A grade of FN (Failing/Non-authorized Incomplete) is awarded to students who did not officially withdraw from the course, but who failed to participate in course activities through the end of the term. The FN grade is to be used when, in the opinion of the instructor, completed assignments or course activities or both were insufficient to make normal evaluation of academic performance possible. Note that once the FN grade is entered, the instructor is required to indicate the date the student last participated in course activity at an academically related activity, i.e., the last date the student completed an exam, quiz, assignment, paper, project, or attended class (if attendance was taken).

Lesson Plan

Key to answering "weaknesses" question is not to respond literally. Identify areas where you can improve.

There's no worse feeling than when you're in an interview and the interviewer asks you a question to which you don't know the answer.

The best way to handle this dreaded debacle is to go into the interview prepared. Familiarize yourself with a few common difficult questions and arm yourself with answers prepared ahead of time.

Check out these tough interview questions and some suggested responses in order to avoid an interview disaster:

Tough question No. 1: "Tell me about yourself."

This is usually the opening question in an interview and it's the perfect moment for you to toot your own horn -- not to tell your life history. Your answers should be a quick rundown of your qualifications and experience. Talk about your education, work history, latest career experience and future goals.

Suggested answer: "I graduated from University X and since then, I have been working in public relations with an agency where I have generated millions of PR hits for my clients. While I've enjoyed working on the agency side, I'm looking to expand my horizons and start doing PR for corporate companies such as this one."

Tough question No. 2: "Why did you leave your last job?"

This is your chance to talk about your experience and your career goals, not to badmouth a former boss or provide a laundry list of reasons for your exit. Instead, focus on what you learned in your previous position and how you are ready to use those skills in a new position.

Suggested answer: "The company just wasn't a good fit for my creativity, but I learned that organizations have distinct personalities just like people do. Now I know where I'll be a better fit."

Tough question No. 3: "Where do you see yourself in five years?"

Let the employer know that you're stable and you want to be with this company for the long haul. Keep your aspirations to take over the firm with which you are interviewing, own your own company, retire at 40 or be married with five children to yourself.

Suggested answer: "I want to secure a civil engineering position with a national firm that concentrates on retail development. Ideally, I would like to work for a young company, such as this one, so I can get in on the ground floor and take advantage of all the opportunities a growing firm has to offer."

Tough question No. 4: "What are your weaknesses?"

The key to answering this age-old question is not to respond literally. Your future employer most likely won't care if your weak spot is that you can't cook, nor do they want to hear the generic responses, like you're "too detail oriented" or "work too hard."

Respond to this query by identifying areas in your work where you can Improve and figure out how they can be assets to a future employer. If you didn't have the opportunity to develop certain skills at your previous job, explain how eager you are to gain that skill in a new position.

Suggested answer: "In my last position, I wasn't able to develop my public-speaking skills. I'd really like to be able to work in a place that will help me get better at giving presentations and talking in front of others."

Tough question No. 5: "Why were you laid off?"

This question will become more common as the economy continues to slow down. It's a tough question, however, especially because many workers aren't told exactly why they were laid off. The best way to tackle this question is to answer as honestly as possible.

Suggested answer: "As I'm sure you're aware, the economy is tough right now and my company felt the effects of it. I was part of a large staff reduction and that's really all I know. I am confident, however, that it had nothing to do with my job performance, as exemplified by my accomplishments. For example..."

Tough question No. 6: "Tell me about the worst boss you ever had."

Never, ever talk badly about your past bosses. A potential boss will anticipate that you'll talk about him or her in the same manner somewhere down the line.

Suggested answer: "While none of my past bosses were awful, there are some who taught me more than others did. I've definitely learned what types of management styles I work with the best."

Tough question No. 7: "How would others describe you?"

You should always be asking for feedback from your colleagues and supervisors in order to gauge your performance; this way, you can honestly answer the question based on their comments. Keep track of the feedback to be able to provide to an employer, if asked. Doing so will also help you identify strengths and weaknesses.

Suggested answer: "My former colleagues have said that I'm easy to do business with and that I always hit the ground running with new projects. I have more specific feedback with me, if you'd like to take a look at it."

Tough question No. 8: "What can you offer me that another person can't?"

This is when you talk about your record of getting things done. Go into specifics from your résumé and portfolio; show an employer your value and how you'd be an asset.

Suggested answer: "I'm the best person for the job. I know there are other candidates who could fill this position, but my passion for excellence sets me apart from the pack. I am committed to always producing the best results. For example..."

Tough question No. 9: "If you could choose any company to work for, where would you go?"

Never say that you would choose any company other than the one where you are interviewing. Talk about the job and the company for which you are being interviewed.

Suggested answer: "I wouldn't have applied for this position if I didn't sincerely want to work with your organization." Continue with specific examples of why you respect the company with which you are interviewing and why you'll be a good fit.

Tough question No. 10: "Would you be willing to take a salary cut?"

Salary is a delicate topic. In today's tough economy though, how much a company can afford to pay you might be the deal breaker in whether or not you are offered a position.

Suggested answer: "I'm making $X now. I understand that the salary range for this position is $XX - $XX. Like most people, I would like to Improve on my salary, but I'm more interested in the job itself than the money. I would be open to negotiating a lower starting salary but would hope that we can revisit the subject in a few months after I've proved myself to you."

Copyright CareerBuilder.com 2009. All rights reserved. The information contained in this article may not be published, broadcast or otherwise distributed without the prior written authority

All About Jobs and Labor

Test your knowledge of Oct. 31 facts with these Halloween trivia questions—answers included!

In Neal Stephenson’s 1995 science fiction novel, The Diamond Age, readers meet Nell, a young girl who comes into possession of a highly advanced book, The Young Lady’s Illustrated Primer. The book is not the usual static collection of texts and images but a deeply immersive tool that can converse with the reader, answer questions, and personalize its content, all in service of educating and motivating a young girl to be a strong, independent individual.

Such a device, even after the introduction of the Internet and tablet computers, has remained in the realm of science fiction—until now. Artificial intelligence, or AI, took a giant leap forward with the introduction in November 2022 of ChatGPT, an AI technology capable of producing remarkably creative responses and sophisticated analysis through human-like dialogue. It has triggered a wave of innovation, some of which suggests we might be on the brink of an era of interactive, super-intelligent tools not unlike the book Stephenson dreamed up for Nell.

Sundar Pichai, Google’s CEO, calls artificial intelligence “more profound than fire or electricity or anything we have done in the past.” Reid Hoffman, the founder of LinkedIn and current partner at Greylock Partners, says, “The power to make positive change in the world is about to get the biggest boost it’s ever had.” And Bill Gates has said that “this new wave of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone.”

Over the last year, developers have released a dizzying array of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. These technologies are rapidly improving, and developers are introducing capabilities that would have been considered science fiction just a few years ago. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism.

In the realm of education, this technology will influence how students learn, how teachers work, and ultimately how we structure our education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to effect “probably the biggest positive transformation that education has ever seen.” But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm.

What Is Generative AI?

Artificial intelligence is a branch of computer science that focuses on creating software capable of mimicking behaviors and processes we would consider “intelligent” if exhibited by humans, including reasoning, learning, problem-solving, and exercising creativity. AI systems can be applied to an extensive range of tasks, including language translation, image recognition, navigating autonomous vehicles, detecting and treating cancer, and, in the case of generative AI, producing content and knowledge rather than simply searching for and retrieving it.

“Foundation models” in generative AI are systems trained on a large dataset to learn a broad base of knowledge that can then be adapted to a range of different, more specific purposes. This learning method is self-supervised, meaning the model learns by finding patterns and relationships in the data it is trained on.

Large Language Models (LLMs) are foundation models that have been trained on a vast amount of text data. For example, the training data for OpenAI’s GPT model consisted of web content, books, Wikipedia articles, news articles, social media posts, code snippets, and more. OpenAI’s GPT-3 models underwent training on a staggering 300 billion “tokens” or word pieces, using more than 175 billion parameters to shape the model’s behavior—nearly 100 times more data than the company’s GPT-2 model had.

By doing this analysis across billions of sentences, LLM models develop a statistical understanding of language: how words and phrases are usually combined, what subjects are typically discussed together, and what tone or style is appropriate in different contexts. That allows it to generate human-like text and perform a wide range of tasks, such as writing articles, answering questions, or analyzing unstructured data.

LLMs include OpenAI’s GPT-4, Google’s PaLM, and Meta’s LLaMA. These LLMs serve as “foundations” for AI applications. ChatGPT is built on GPT-3.5 and GPT-4, while Bard uses Google’s Pathways Language Model 2 (PaLM 2) as its foundation.

Some of the best-known applications are:

ChatGPT 3.5. The free version of ChatGPT released by OpenAI in November 2022. It was trained on data only up to 2021, and while it is very fast, it is prone to inaccuracies.

ChatGPT 4.0. The existing version of ChatGPT, which is more powerful and accurate than ChatGPT 3.5 but also slower, and it requires a paid account. It also has extended capabilities through plug-ins that provide it the ability to interface with content from websites, perform more sophisticated mathematical functions, and access other services. A new Code Interpreter feature gives ChatGPT the ability to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends.

Microsoft Bing Chat. An iteration of Microsoft’s Bing search engine that is enhanced with OpenAI’s ChatGPT technology. It can browse websites and offers source citations with its results.

Google Bard. Google’s AI generates text, translates languages, writes different kinds of creative content, and writes and debugs code in more than 20 different programming languages. The tone and style of Bard’s replies can be finetuned to be simple, long, short, professional, or casual. Bard also leverages Google Lens to analyze images uploaded with prompts.

Anthropic Claude 2. A chatbot that can generate text, summarize content, and perform other tasks, Claude 2 can analyze texts of roughly 75,000 words—about the length of The Great Gatsby—and generate responses of more than 3,000 words. The model was built using a set of principles that serve as a sort of “constitution” for AI systems, with the aim of making them more helpful, honest, and harmless.

These AI systems have been improving at a remarkable pace, including in how well they perform on assessments of human knowledge. OpenAI’s GPT-3.5, which was released in March 2022, only managed to score in the 10th percentile on the bar exam, but GPT-4.0, introduced a year later, made a significant leap, scoring in the 90th percentile. What makes these feats especially impressive is that OpenAI did not specifically train the system to take these exams; the AI was able to come up with the correct answers on its own. Similarly, Google’s medical AI model substantially improved its performance on a U.S. Medical Licensing Examination practice test, with its accuracy rate jumping to 85 percent in March 2021 from 33 percent in December 2020.

These two examples prompt one to ask: if AI continues to Improve so rapidly, what will these systems be able to achieve in the next few years? What’s more, new studies challenge the assumption that AI-generated responses are stale or sterile. In the case of Google’s AI model, physicians preferred the AI’s long-form answers to those written by their fellow doctors, and nonmedical study participants rated the AI answers as more helpful. Another study found that participants preferred a medical chatbot’s responses over those of a physician and rated them significantly higher, not just for quality but also for empathy. What will happen when “empathetic” AI is used in education?

Other studies have looked at the reasoning capabilities of these models. Microsoft researchers suggest that newer systems “exhibit more general intelligence than previous AI models” and are coming “strikingly close to human-level performance.” While some observers question those conclusions, the AI systems display an increasing ability to generate coherent and contextually appropriate responses, make connections between different pieces of information, and engage in reasoning processes such as inference, deduction, and analogy.

Despite their prodigious capabilities, these systems are not without flaws. At times, they churn out information that might sound convincing but is irrelevant, illogical, or entirely false—an anomaly known as “hallucination.” The execution of certain mathematical operations presents another area of difficulty for AI. And while these systems can generate well-crafted and realistic text, understanding why the model made specific decisions or predictions can be challenging.

The Importance of Well-Designed Prompts

Using generative AI systems such as ChatGPT, Bard, and Claude 2 is relatively simple. One has only to type in a request or a task (called a prompt), and the AI generates a response. Properly constructed prompts are essential for getting useful results from generative AI tools. You can ask generative AI to analyze text, find patterns in data, compare opposing arguments, and summarize an article in different ways (see sidebar for examples of AI prompts).

One challenge is that, after using search engines for years, people have been preconditioned to phrase questions in a certain way. A search engine is something like a helpful librarian who takes a specific question and points you to the most relevant sources for possible answers. The search engine (or librarian) doesn’t create anything new but efficiently retrieves what’s already there.

Generative AI is more akin to a competent intern. You provide a generative AI tool instructions through prompts, as you would to an intern, asking it to complete a task and produce a product. The AI interprets your instructions, thinks about the best way to carry them out, and produces something original or performs a task to fulfill your directive. The results aren’t pre-made or stored somewhere—they’re produced on the fly, based on the information the intern (generative AI) has been trained on. The output often depends on the precision and clarity of the instructions (prompts) you provide. A vague or poorly defined prompt might lead the AI to produce less relevant results. The more context and direction you provide it, the better the result will be. What’s more, the capabilities of these AI systems are being enhanced through the introduction of versatile plug-ins that equip them to browse websites, analyze data files, or access other services. Think of this as giving your intern access to a group of experts to help accomplish your tasks.

One strategy in using a generative AI tool is first to tell it what kind of expert or persona you want it to “be.” Ask it to be an expert management consultant, a skilled teacher, a writing tutor, or a copy editor, and then provide it a task.

Prompts can also be constructed to get these AI systems to perform complex and multi-step operations. For example, let’s say a teacher wants to create an adaptive tutoring program—for any subject, any grade, in any language—that customizes the examples for students based on their interests. She wants each lesson to culminate in a short-response or multiple-choice quiz. If the student answers the questions correctly, the AI tutor should move on to the next lesson. If the student responds incorrectly, the AI should explain the concept again, but using simpler language.

Previously, designing this kind of interactive system would have required a relatively sophisticated and expensive software program. With ChatGPT, however, just giving those instructions in a prompt delivers a serviceable tutoring system. It isn’t perfect, but remember that it was built virtually for free, with just a few lines of English language as a command. And nothing in the education market today has the capability to generate almost limitless examples to connect the lesson concept to students’ interests.

Chained prompts can also help focus AI systems. For example, an educator can prompt a generative AI system first to read a practice guide from the What Works Clearinghouse and summarize its recommendations. Then, in a follow-up prompt, the teacher can ask the AI to develop a set of classroom activities based on what it just read. By curating the source material and using the right prompts, the educator can anchor the generated responses in evidence and high-quality research.

However, much like fledgling interns learning the ropes in a new environment, AI does commit occasional errors. Such fallibility, while inevitable, underlines the critical importance of maintaining rigorous oversight of AI’s output. Monitoring not only acts as a crucial checkpoint for accuracy but also becomes a vital source of real-time feedback for the system. It’s through this iterative refinement process that an AI system, over time, can significantly minimize its error rate and increase its efficacy.

Uses of AI in Education

In May 2023, the U.S. Department of Education released a report titled Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. The department had conducted listening sessions in 2022 with more than 700 people, including educators and parents, to gauge their views on AI. The report noted that “constituents believe that action is required now in order to get ahead of the expected increase of AI in education technology—and they want to roll up their sleeves and start working together.” People expressed anxiety about “future potential risks” with AI but also felt that “AI may enable achieving educational priorities in better ways, at scale, and with lower costs.”

AI could serve—or is already serving—in several teaching-and-learning roles:

Instructional assistants. AI’s ability to conduct human-like conversations opens up possibilities for adaptive tutoring or instructional assistants that can help explain difficult concepts to students. AI-based feedback systems can offer constructive critiques on student writing, which can help students fine-tune their writing skills. Some research also suggests certain kinds of prompts can help children generate more fruitful questions about learning. AI models might also support customized learning for students with disabilities and provide translation for English language learners.

Teaching assistants. AI might tackle some of the administrative tasks that keep teachers from investing more time with their peers or students. Early uses include automated routine tasks such as drafting lesson plans, creating differentiated materials, designing worksheets, developing quizzes, and exploring ways of explaining complicated academic materials. AI can also provide educators with recommendations to meet student needs and help teachers reflect, plan, and Improve their practice.

Parent assistants. Parents can use AI to generate letters requesting individualized education plan (IEP) services or to ask that a child be evaluated for gifted and talented programs. For parents choosing a school for their child, AI could serve as an administrative assistant, mapping out school options within driving distance of home, generating application timelines, compiling contact information, and the like. Generative AI can even create bedtime stories with evolving plots tailored to a child’s interests.

Administrator assistants. Using generative AI, school administrators can draft various communications, including materials for parents, newsletters, and other community-engagement documents. AI systems can also help with the difficult tasks of organizing class or bus schedules, and they can analyze complex data to identify patterns or needs. ChatGPT can perform sophisticated sentiment analysis that could be useful for measuring school-climate and other survey data.

Though the potential is great, most teachers have yet to use these tools. A Morning Consult and EdChoice poll found that while 60 percent say they’ve heard about ChatGPT, only 14 percent have used it in their free time, and just 13 percent have used it at school. It’s likely that most teachers and students will engage with generative AI not through the platforms themselves but rather through AI capabilities embedded in software. Instructional providers such as Khan Academy, Varsity Tutors, and DuoLingo are experimenting with GPT-4-powered tutors that are trained on datasets specific to these organizations to provide individualized learning support that has additional guardrails to help protect students and enhance the experience for teachers.

Google’s Project Tailwind is experimenting with an AI notebook that can analyze student notes and then develop study questions or provide tutoring support through a chat interface. These features could soon be available on Google Classroom, potentially reaching over half of all U.S. classrooms. Brisk Teaching is one of the first companies to build a portfolio of AI services designed specifically for teachers—differentiating content, drafting lesson plans, providing student feedback, and serving as an AI assistant to streamline workflow among different apps and tools.

Providers of curriculum and instruction materials might also include AI assistants for instant help and tutoring tailored to the companies’ products. One example is the edX Xpert, a ChatGPT-based learning assistant on the edX platform. It offers immediate, customized academic and customer support for online learners worldwide.

Regardless of the ways AI is used in classrooms, the fundamental task of policymakers and education leaders is to ensure that the technology is serving sound instructional practice. As Vicki Phillips, CEO of the National Center on Education and the Economy, wrote, “We should not only think about how technology can assist teachers and learners in improving what they’re doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI.”

Challenges and Risks

Along with these potential benefits come some difficult challenges and risks the education community must navigate:

Student cheating. Students might use AI to solve homework problems or take quizzes. AI-generated essays threaten to undermine learning as well as the college-entrance process. Aside from the ethical issues involved in such cheating, students who use AI to do their work for them may not be learning the content and skills they need.

Bias in AI algorithms. AI systems learn from the data they are trained on. If this data contains biases, those biases can be learned and perpetuated by the AI system. For example, if the data include student-performance information that’s biased toward one ethnicity, gender, or socioeconomic segment, the AI system could learn to favor students from that group. Less cited but still important are potential biases around political ideology and possibly even pedagogical philosophy that may generate responses not aligned to a community’s values.

Privacy concerns. When students or educators interact with generative-AI tools, their conversations and personal information might be stored and analyzed, posing a risk to their privacy. With public AI systems, educators should refrain from inputting or exposing sensitive details about themselves, their colleagues, or their students, including but not limited to private communications, personally identifiable information, health records, academic performance, emotional well-being, and financial information.

Decreased social connection. There is a risk that more time spent using AI systems will come at the cost of less student interaction with both educators and classmates. Children may also begin turning to these conversational AI systems in place of their friends. As a result, AI could intensify and worsen the public health crisis of loneliness, isolation, and lack of connection identified by the U.S. Surgeon General.

Overreliance on technology. Both teachers and students face the risk of becoming overly reliant on AI-driven technology. For students, this could stifle learning, especially the development of critical thinking. This challenge extends to educators as well. While AI can expedite lesson-plan generation, speed does not equate to quality. Teachers may be tempted to accept the initial AI-generated content rather than devote time to reviewing and refining it for optimal educational value.

Equity issues. Not all students have equal access to computer devices and the Internet. That imbalance could accelerate a widening of the achievement gap between students from different socioeconomic backgrounds.

Many of these risks are not new or unique to AI. Schools banned calculators and cellphones when these devices were first introduced, largely over concerns related to cheating. Privacy concerns around educational technology have led lawmakers to introduce hundreds of bills in state legislatures, and there are growing tensions between new technologies and existing federal privacy laws. The concerns over bias are understandable, but similar scrutiny is also warranted for existing content and materials that rarely, if ever, undergo review for racial or political bias.

In light of these challenges, the Department of Education has stressed the importance of keeping “humans in the loop” when using AI, particularly when the output might be used to inform a decision. As the department encouraged in its 2023 report, teachers, learners, and others need to retain their agency. AI cannot “replace a teacher, a guardian, or an education leader as the custodian of their students’ learning,” the report stressed.

Policy Challenges with AI

Policymakers are grappling with several questions related to AI as they seek to strike a balance between supporting innovation and protecting the public interest (see sidebar). The speed of innovation in AI is outpacing many policymakers’ understanding, let alone their ability to develop a consensus on the best ways to minimize the potential harms from AI while maximizing the benefits. The Department of Education’s 2023 report describes the risks and opportunities posed by AI, but its recommendations amount to guidance at best. The White House released a Blueprint for an AI Bill of Rights, but it, too, is more an aspirational statement than a governing document. Congress is drafting legislation related to AI, which will help generate needed debate, but the path to the president’s desk for signature is murky at best.

It is up to policymakers to establish clearer rules of the road and create a framework that provides consumer protections, builds public trust in AI systems, and establishes the regulatory certainty companies need for their product road maps. Considering the potential for AI to affect our economy, national security, and broader society, there is no time to waste.

Why AI Is Different

It is wise to be skeptical of new technologies that claim to revolutionize learning. In the past, prognosticators have promised that television, the computer, and the Internet, in turn, would transform education. Unfortunately, the heralded revolutions fell short of expectations. 

There are some early signs, though, that this technological wave might be different in the benefits it brings to students, teachers, and parents. Previous technologies democratized access to content and resources, but AI is democratizing a kind of machine intelligence that can be used to perform a myriad of tasks. Moreover, these capabilities are open and affordable—nearly anyone with an Internet connection and a phone now has access to an intelligent assistant. 

Generative AI models keep getting more powerful and are improving rapidly. The capabilities of these systems months or years from now will far exceed their current capacity. Their capabilities are also expanding through integration with other expert systems. Take math, for example. GPT-3.5 had some difficulties with certain basic mathematical concepts, but GPT-4 made significant improvement. Now, the incorporation of the Wolfram plug-in has nearly erased the remaining limitations. 

It’s reasonable to anticipate that these systems will become more potent, more accessible, and more affordable in the years ahead. The question, then, is how to use these emerging capabilities responsibly to Improve teaching and learning. 

The paradox of AI may lie in its potential to enhance the human, interpersonal element in education. Aaron Levie, CEO of Box, a Cloud-based content-management company, believes that AI will ultimately help us attend more quickly to those important tasks “that only a human can do.” Frederick Hess, director of education policy studies at the American Enterprise Institute, similarly asserts that “successful schools are inevitably the product of the relationships between adults and students. When technology ignores that, it’s bound to disappoint. But when it’s designed to offer more coaching, free up time for meaningful teacher-student interaction, or offer students more personalized feedback, technology can make a significant, positive difference.” 

Technology does not revolutionize education; humans do. It is humans who create the systems and institutions that educate children, and it is the leaders of those systems who decide which tools to use and how to use them. Until those institutions modernize to accommodate the new possibilities of these technologies, we should expect incremental improvements at best. As Joel Rose, CEO of New Classrooms Innovation Partners, noted, “The most urgent need is for new and existing organizations to redesign the student experience in ways that take full advantage of AI’s capabilities.”

While past technologies have not lived up to hyped expectations, AI is not merely a continuation of the past; it is a leap into a new era of machine intelligence that we are only beginning to grasp. While the immediate implementation of these systems is imperfect, the swift pace of improvement holds promising prospects. The responsibility rests with human intervention—with educators, policymakers, and parents to incorporate this technology thoughtfully in a manner that optimally benefits teachers and learners. Our collective ambition should not focus solely or primarily on averting potential risks but rather on articulating a vision of the role AI should play in teaching and learning—a game plan that leverages the best of these technologies while preserving the best of human relationships.

Policy Matters

Officials and lawmakers must grapple with several questions related to AI to protect students and consumers and establish the rules of the road for companies. Key issues include:

Risk management framework: What is the optimal framework for assessing and managing AI risks? What specific requirements should be instituted for higher-risk applications? In education, for example, there is a difference between an AI system that generates a lesson trial and an AI system grading a test that will determine a student’s admission to a school or program. There is growing support for using the AI Risk Management Framework from the U.S. Commerce Department’s National Institute of Standards and Technology as a starting point for building trustworthiness into the design, development, use, and evaluation of AI products, services, and systems.

Licensing and certification: Should the United States require licensing and certification for AI models, systems, and applications? If so, what role could third-party audits and certifications play in assessing the safety and reliability of different AI systems? Schools and companies need to begin thinking about responsible AI practices to prepare for potential certification systems in the future.

Centralized vs. decentralized AI governance: Is it more effective to establish a central AI authority or agency, or would it be preferable to allow individual sectors to manage their own AI-related issues? For example, regulating AI in autonomous vehicles is different from regulating AI in drug discovery or intelligent tutoring systems. Overly broad, one-size-fits-all frameworks and mandates may not work and could slow innovation in these sectors. In addition, it is not clear that many agencies have the authority or expertise to regulate AI systems in diverse sectors.

Privacy and content moderation: Many of the new AI systems pose significant new privacy questions and challenges. How should existing privacy and content-moderation frameworks, such as the Family Educational Rights and Privacy Act (FERPA), be adapted for AI, and which new policies or frameworks might be necessary to address unique challenges posed by AI?

Transparency and disclosure: What degree of transparency and disclosure should be required for AI models, particularly regarding the data they have been trained on? How can we develop comprehensive disclosure policies to ensure that users are aware when they are interacting with an AI service?

How do I get it to work? Generative AI Example Prompts

Unlike traditional search engines, which use keyword indexing to retrieve existing information from a vast collection of websites, generative AI synthesizes the same information to create content based on prompts that are inputted by human users. With generative AI a new technology to the public, writing effective prompts for tools like ChatGPT may require trial and error. Here are some ideas for writing prompts for a variety of scenarios using generative AI tools:

Adaptive Tutoring

You are the StudyBuddy, an adaptive tutor. Your task is to provide a lesson on the basics of a subject followed by a quiz that is either multiple choice or a short answer. After I respond to the quiz, please grade my answer. Explain the correct answer. If I get it right, move on to the next lesson. If I get it wrong, explain the concept again using simpler language. To personalize the learning experience for me, please ask what my interests are. Use that information to make relevant examples throughout.

Mr. Ranedeer: Your Personalized AI Tutor

Coding and prompt engineering. Can configure for depth (Elementary – Postdoc), Learning Styles (Visual, Verbal, Active, Intuitive, Reflective, Global), Tone Styles (Encouraging, Neutral, Informative, Friendly, Humorous), Reasoning Frameworks (Deductive, Inductive, Abductive, Analogous, Casual). Template.

Socratic Tutor

You are a tutor that always responds in the Socratic style. You *never* provide the student the answer but always try to ask just the right question to help them learn to think for themselves. You should always tune your question to the interest and knowledge of the student, breaking down the problem into simpler parts until it’s at just the right level for them.

Writing Feedback

I want you to act as an AI writing tutor. I will provide you with a student who needs help improving their writing, and your task is to use artificial intelligence tools, such as natural language processing, to provide the student feedback on how they can Improve their composition. You should also use your rhetorical knowledge and experience about effective writing techniques in order to suggest ways that the student can better express their thoughts and ideas in written form.

Quiz Generator

You are a quiz creator of highly diagnostic quizzes. You will make good low-stakes tests and diagnostics. You will then ask me two questions. First, (1) What, specifically, should the quiz test? Second, (2) For which audience is the quiz? Once you have my answers, you will construct several multiple-choice questions to quiz the audience on that topic. The questions should be highly relevant and go beyond just facts. Multiple choice questions should include plausible, competitive alternate responses and should not include an “all of the above” option. At the end of the quiz, you will provide an answer key and explain the right answer.

Example Generator

I would like you to act as an example generator for students. When confronted with new and complex concepts, adding many and varied examples helps students better understand those concepts. I would like you to ask what concept I would like examples of and what level of students I am teaching. You will look up the concept and then provide me with four different and varied accurate examples of the concept in action.

HBS Case Study

You will write a Harvard Business School case on the syllabu of Google managing AI, when subject to the Innovator’s Dilemma. Chain of thought: Step 1. Consider how these concepts relate to Google. Step 2: Write a case that revolves around a dilemma at Google about releasing a generative AI system that could compete with search.

What Questions Should I Ask?

What additional questions would a person seeking mastery of this syllabu ask?

Ground Lessons in Rigor

Read a WWC practice guide. Create a series of lessons over five days that are based on Recommendation 6. Create a 45-minunte lesson plan for Day 4.

Rewrite Parent Communications

The following is a draft letter to parents from a superintendent. Step 1: Rewrite it to make it easier to understand and more persuasive about the value of assessments. Step 2. Translate it into Spanish.

Request IEP Services

Write me a letter requesting the school district provide a 1:1 classroom aid be added to my 13-year-old son’s IEP. Base it on Virginia special education law and the least restrictive environment for a child with diagnoses of a Traumatic Brain Injury, PTSD, ADHD, and significant intellectual delay.

1. How do I apply for a certification?

2. What are the fees for certification?

3. How long is the exam, and how many questions are there?

4. Where is my certification test invitation?

6. How do I schedule my certification exam?

8. What happens after I take a certification exam?

9. How do I request a retest for a certification exam?

10. How do I renew my certification?

12. How do I access my digital badge?

13. Additional Questions

Like most people, you’re probably eager to make progress in your career.

But sometimes, as you acquire more experience and take on additional responsibilities, you become so incredibly busy you lose track of why you’re working so hard in the first place. And given your efforts, you might wonder why you’re not moving closer to your goals.

Before spending another minute on your to-do list, it’s imperative that you pause and ask yourself one simple yet important question: Why am I doing this?

And by “this,” I mean each activity, behavior, and environment you choose to engage in. Consider every aspect of your professional world: your job, role and responsibilities, industry, how and with whom you spend your time, and when, where, and how you work.

Though asking yourself that question might seem silly initially, your answer matters because it can help you gain more awareness about your actions and understand whether you’re making the right decisions to move you closer to your goals.

Ideally, your answer to the question is:

• Because it gives me knowledge
• Because it provides income
• Because it fulfills me, and
• Because it aligns with and supports my goals.

But, if your answer is:

• Because I’ve always done it
• Because someone else expects me to, or
• I’m not sure

You may have outgrown that activity, association, role, or season in your career, or strayed from doing what matters most.

Though realizing this can be jarring, there is good news:

First, discovering this enables you to see and acknowledge that you’re in a career rut.

Though it seems obvious, many people don’t realize when they’re in a rut, career-wise. They busy themselves being busy, ignoring the red flags of their discontent or using their fear to avoid confronting their reality. But the first step in solving a problem is identifying it as a problem.

Second, it provides greater clarity around what you want (and don’t want).

Asking yourself, “Why am I doing this?” leads to another essential question: “What do I want?” Now is the time to answer that question honestly—even if the answer differs from what you thought it might (or should) be. Equally as valuable is what your awareness tells you you don’t (or no longer) want. Clarity is about focus, so drill down and get specific.

Third, it helps you take action that aligns with and supports your goals.

Without alignment, you’ll forever spin your wheels and waste your efforts on being busy but not productive. When you understand why you’re doing what you’re doing, you ensure your choices reinforce that. True career progress comes from taking action aligned with what matters most to you.

Remember, every decision you make, from the profession you pursue to the people you interact with to the environment you operate in, should be an intentional choice that aligns with and support your goals.

If it is, great, carry on.

But if it isn’t, asking and answering this question can be the wake-up call you need to make much-needed changes.