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A2.2 · Examine how innovations and AI affect society and careers

Learn to examine how innovations and ai affect society and careers through clear examples and targeted practice.

Ontario Grade 9 Science

STEM Skills, Careers, and Connections

A Grade 9 guide to examining benefits, risks, evidence, and changing work

Think about a phone app that identifies a plant from a picture. It may help someone learn about local plants, but its answer could be wrong. People still need to decide whether to trust it and what to do next. This is one way an innovation can affect learning, decisions, and work. An innovation is a new or improved idea, product, or way of doing something. Artificial intelligence, or AI, is computer technology designed to perform tasks that can include finding patterns, making predictions, or producing responses. AI tools are made and used by people; they do not guarantee correct answers. The central question in this lesson is: how can innovations and AI affect society and careers, and what evidence helps us judge those effects?

What you will learn

Define innovation and artificial intelligence (AI) in clear, practical terms.
Examine how an innovation or AI tool can affect people and society.
Describe ways that technologies can change tasks and skills in careers.
Separate evidence about how a tool works from judgments about whether it should be used.

1. From everyday tool to science question

People use innovations in many parts of life. A health worker might use software to help organize information. A chemist might use a computer to sort results from a study. A person studying space might use software to help review images collected by a telescope. These examples connect technology with biology, chemistry, and space science, but the tools do not replace the need to check information.

A useful examination begins with a clear question. For example: What task does the tool help with? Who uses it? Who may benefit, and who may face a problem? What evidence supports claims about its effects? A benefit is a helpful result. A risk is a possible harmful result. The same tool can have both.

AI is not one single tool. Different AI systems are designed for different tasks. Some sort information; others make predictions or create text or images. A result from an AI system is an output. An output should be checked, especially when people could be harmed by an error.

Innovation means a new or improved idea, product, or process.
AI is computer technology designed to carry out tasks such as finding patterns or producing responses.
Ask who is affected, what changes, and what evidence supports a claim.

2. A model for examining effects

A model is a simplified way to show or explain something. The flow diagram in the examples uses a simple pattern: a tool is used for a task, which may lead to effects, and people respond to those effects. This model helps organize questions. It does not predict every result or prove that a tool caused an effect.

Consider a hypothetical plant-identification app. A learner takes a picture, and the app suggests a name. The learner can compare that suggestion with a trusted field guide or ask a knowledgeable adult. The app may make information easier to access, but a poor picture or an unfamiliar plant could lead to a mistaken suggestion. The model highlights a possible benefit and a possible limitation without claiming that every app performs the same way.

Evidence is information collected or reported in a way that helps answer a question. For a technology claim, evidence might include a carefully described test, published research, or reports from people who use the tool. A claim such as “this app saves time” needs evidence about the task and the people tested. One person’s experience may be useful, but it does not show what will happen for everyone.

A social or ethical judgment is a decision about what is fair, safe, or acceptable for people. Evidence can inform that judgment, but it does not make the decision by itself. For example, evidence might show that a tool sometimes gives incorrect suggestions. People and organizations must still decide what checks are needed before using it.

A model organizes thinking but leaves out details.
Evidence supports or challenges claims; a social or ethical judgment considers what people ought to do.
Check the source, the task tested, and whether the evidence applies to the people affected.

3. Work, careers, and changing tasks

A career is a type of work that may involve many different tasks. An innovation can change how some tasks are done without removing every part of a job. For instance, software may help sort information, while a worker checks whether the information is suitable and explains it to other people. This can change which skills are useful.

A skill is an ability developed through learning or practice. When tools change, workers may need to learn how to use them, check their outputs, explain decisions, or handle tasks the tools cannot do well. Some people may gain new opportunities, while others may need training or face changes to their work. Effects can differ across workplaces and communities.

Do not assume that a tool always creates jobs or always removes them. Those are broad claims that require evidence. Ask which tasks changed, who benefits, what new skills are needed, and whether workers have access to training. A fair examination considers more than the tool’s speed or convenience.

Jobs contain tasks, and technologies may change some tasks more than others.
Workers may need new or different skills when tools change.
The effects on careers can vary; avoid claims that apply to all workers without evidence.

4. Examine a claim carefully

Use a repeatable set of questions when examining an innovation or AI tool. First, name the tool and the task it is meant to support. Next, identify the people affected. Then consider possible benefits and risks. Look for evidence, and note what it does not tell you. Finally, separate what the evidence shows from what people decide should happen.

For example, a report may describe a trial of a tool in one workplace. That may provide evidence about that setting, but it may not show what would happen in another workplace. A small or limited test can be informative while still leaving questions. Being clear about limits makes an examination more trustworthy.

The examples below use hypothetical situations to practise this approach. They are not reports of real tests or proof that a particular product has a particular effect. Their flow diagrams are planning models, not measured results.

Name the task, people affected, possible effects, and evidence.
State limits instead of treating one example as proof for every situation.
Evidence helps inform decisions, but social and ethical choices involve values and responsibilities.

Questions for examining a technology

Focus	Question to ask
Task	What is the tool meant to help someone do?
People	Who may benefit or face a problem?
Evidence	What supports the claim, and what are its limits?
Careers	Which tasks or skills might change?
Judgment	What decision is needed beyond the evidence?

Worked example

A plant-identification app

A school is considering whether learners should use a hypothetical AI app to suggest plant names from photographs. Examine one possible benefit, one risk, and a sensible way to check the app’s suggestions.

Checking an AI plant suggestion

Hypothetical process model, not test data. It does not show how accurate an app is or represent every app.

Name the task
The app is intended to suggest a plant name from an image. Naming the task keeps the discussion focused on what the tool is designed to do, rather than assuming it can identify every plant correctly.
Consider effects
A possible benefit is quicker access to a suggestion. A risk is that an unclear photograph could lead to a wrong suggestion. These are possibilities in this hypothetical example, not measured results.
Plan a check
Learners can compare a suggestion with a trusted field guide or ask a knowledgeable adult. The app’s output is a starting point for checking, not proof that the identification is correct.
State the limit
This example does not establish how accurate any real app is. To make a claim about a particular app, people would need evidence from a suitable test and would need to describe what was tested.

Answer: The app may help learners access a plant-name suggestion, but it could also give an incorrect suggestion. Comparing outputs with a trusted source is a sensible check. Evidence about a real app would be needed to judge its performance.

Check: The answer separates a possible benefit and risk from a claim about actual accuracy.

Worked example

AI support in a science career

Imagine a chemistry team uses hypothetical AI software to sort many entries in a research database. Examine how this could affect a worker’s tasks and identify a limit of the example.

AI-supported information work

Hypothetical task model, not measured evidence. It simplifies a research worker’s responsibilities and does not show every step.

Identify the changed task
The software is used to sort entries. If it does that task, a worker may spend less time arranging information and more time reviewing whether the entries are useful.
Identify relevant skills
Workers may need to understand the research question, use the software, and check its output. These skills matter because a sorted list is not automatically a correct or useful conclusion.
Consider people and limits
The software might support some tasks, but the example does not show that it replaces a worker or changes every chemistry career. Evidence from a specific workplace would be needed to support such claims.

Answer: The tool could change how a worker organizes information and make checking and interpretation more important. The example cannot show what happens in all chemistry workplaces or whether a particular tool saves time.

Check: The answer discusses task changes without claiming that a whole career is replaced.

Worked example

A proposed AI tool for space images

A hypothetical space-science team is considering software that flags images that may need closer review. Explain one possible benefit, one concern, and what evidence the team should seek before relying on it.

Reviewing flagged space images

Hypothetical process model, not real space data. It does not show measured accuracy or the full work of a space-science team.

Describe the possible benefit
Flagging images could help a team decide which images to review first. This is a possible benefit in the scenario, not evidence that the software actually works well.
Describe a concern
The software might fail to flag an image that deserves attention, or flag an image that does not. A person should not treat a flag as a final scientific conclusion.
Ask for relevant evidence
The team should look for a careful test using images suited to the task, with a clear description of how the software’s suggestions were checked. The test’s limits should be reported too.
Separate evidence and judgment
Test evidence could help describe the tool’s performance in the tested setting. The team must still decide how much human review is needed and whether relying on the tool is appropriate.

Answer: The tool might help prioritize image review, but it could miss or wrongly flag images. A suitable, clearly described test could provide evidence about its performance in that setting. Decisions about human review remain a responsibility of the people using it.

Check: The answer treats the AI output as support for review, not as proof or a final decision.

Common mistakes and how to avoid them

Assuming an AI output must be correct because a computer produced it.

Correction: Treat the output as information to check. A tool can make errors or have limits.

Saying that AI always replaces workers or always creates jobs.

Correction: Examine specific tasks and evidence. Effects can differ among careers and workplaces.

Treating one person’s experience as proof of what will happen to everyone.

Correction: State who and what the evidence covers, and avoid claims broader than the evidence supports.

Confusing evidence with a decision about what is fair or acceptable.

Correction: Evidence helps people understand possible effects. People still make social and ethical judgments.

Lesson summary

Innovations are new or improved ideas, products, or processes; AI is computer technology designed to perform tasks such as finding patterns or producing responses.
Technologies can affect people and society through both benefits and risks.
Innovations may change tasks and skills in careers, but effects vary and need evidence.
Models simplify situations. Evidence supports claims, while social and ethical judgments guide decisions.

Check your understanding

Question 1

A school says an AI app always identifies plants correctly because it gave one learner a useful suggestion. What is the strongest response?

One useful suggestion proves that the app is always correct.
The example is limited; a suitable test is needed to judge the app’s performance.
A computer output is evidence that no checking is needed.
The app cannot affect learning because it is not a person.

Show answer and explanation

The example is limited; a suitable test is needed to judge the app’s performance.

One example does not establish that an app is always correct. A suitable test and a clear account of its limits would provide stronger evidence.

Question 2

A workplace uses software to sort information. Which statement best examines a possible career effect?

The software must remove every job in that workplace.
The software cannot affect workers because it only sorts information.
Some tasks may change, and workers may need to check outputs or learn new skills.
Every worker will have exactly the same experience.

Show answer and explanation

Some tasks may change, and workers may need to check outputs or learn new skills.

A tool may change some tasks and skills without determining what happens to every worker or job.

Question 3

A test suggests an AI tool made errors in the setting examined. What is a social or ethical question people might still need to decide?

Whether the tool’s output should be checked by a person before use.
Whether the test result is an opinion rather than evidence in every case.
Whether the tool should be described as correct without more information.
Whether evidence can replace all decisions about people.

Show answer and explanation

Whether the tool’s output should be checked by a person before use.

Evidence about errors can inform a decision, but people still need to decide what safeguards are appropriate.

Key terms

Artificial intelligence (AI): Computer technology designed to perform tasks such as finding patterns, making predictions, or producing responses.
Evidence: Information collected or reported in a way that helps answer a question or support a claim.
Innovation: A new or improved idea, product, or way of doing something.
Model: A simplified representation used to organize or explain an idea or situation.
Risk: A possible harmful result or problem.
Skill: An ability developed through learning or practice.
Social or ethical judgment: A decision about what is fair, safe, or acceptable for people.

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About this lesson and its review

Published by DoAssignment. This reviewed lesson follows Ontario Grade 9 Science (SNC1W), expectation A2.2. It is a study resource, not an official curriculum publication.

Before publication, content is checked for structure, mathematical or chemical notation, calculations, course boundaries, and readability. Errors can still occur, so corrections are welcomed.

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