Month: March 2026

Artificial intelligence and social media: How should digital citizens in Canadian education respond when “artificial intelligence garbage” drowns the flow of information?

One of the biggest changes brought about by generative artificial intelligence in the Canadian social media environment is the so-called “AI garbage”: a large amount of low-cost content that seems to be “information/news/knowledge” is quickly generated and poured into the information flow. It is not necessarily “completely fake”, but common problems include: unknown source, weak evidence, sensational titles, and the use of “real” pictures or tones to create a sense of authority, which ultimately misleads people into believing that they “see the truth”.

1) An example of AI wasting information and spreading misinformation that I observed.

On the TikTok short video platform, I often see some short videos similar to the first-person perspective or live images: using materials that look like first-person perspective or disaster scenes, such as car accident scenes or disaster scenes. This kind of content can usually give a strong conclusion, but lacks a clear source and verifiable original link. Two reactions soon emerged in the comment section: one was anger and partiality, and the other was spreading fear without a clear factual basis, such as “I know, it’s near my home, or I heard it from a friend in that area”, thus further amplifying the uncertain information.

This is a typical risk of AI mistakes: it pushes unreliable content to more people through “the appearance of news + exaggerated emotions + platform recommendation mechanism”, thus amplifying misinformation.

MediaSmarts emphasized in the materials of Media Literacy Week that artificial intelligence-driven false information has attracted wider attention because it makes the content “look more credible, thus increasing the possibility of misleading and dissemination”.

2) How will this affect public opinion?

The impact of artificial intelligence’s bad behavior on public opinion is not only “someone has been deceived”, but also changes the structure of social discussion:

Decreased trust: When people keep seeing content that “looks like news but cannot be verified”, they will eventually lose trust in the media, institutions and professionals, and eventually “no longer trust anyone”.

Accelerated polarization: The emotional expression in short videos easily simplifies complex problems into simple opposition, and transforms public discussion from “understanding the problem” to “choose the side”.

Make error messages more difficult to correct: once the content is forwarded, edited and reprocessed, it is difficult to trace its original source; the speed of correction usually cannot keep up with the speed of dissemination.

Create “information pollution”: Even if not all information is false, low-quality and sourceless content will squeeze the information space, making truly reliable information more difficult to see.

From the perspective of digital citizens, the risk is that we may inadvertently participate in the spread of misinformation through likes, comments and shares.

3) Can Canada’s current policy/research solve this problem?

Canadian research and policy discussions have begun to address the issue head-on, but there is still a major gap.

Insufficient tags: DAIS research shows that small “AI-generated” tags have little impact on users’ trust or sharing behavior; stronger full-screen prompts are more effective, but the platform usually does not adopt them.

This means that relying solely on platform “light reminders” is unlikely to resist the spread of AI garbage.

The national strategy emphasizes “skills and governance”, but implementation requires the cooperation of the education system: DAIS lists “trusted governance + skills and talent + sovereign ability” as one of the pillars in its proposal to update Canada’s artificial intelligence strategy.

This also shows that if the education system does not regard media literacy/artificial intelligence literacy as basic skills, the policy will be difficult to implement.

The conclusion is that although policies and research are advancing, in the face of the phenomenon of “scale, low cost and platform amplification” of AI, the education department must supplement it through “operable media literacy training”.

4) The media literacy course I proposed is aimed at ninth-grade high school students and lasts 40-50 minutes.

Goal: To enable students to stop when encountering AI’s bad remarks, check the source and evaluate its credibility, instead of being driven by emotions to forward.

Course name:

“Stop-Check-Decision: Identifying AI Mistakes and Verifying Information”

Learning Objectives: Students will be able to explain what artificial intelligence mistakes are and their misleadingness. Use a simple verification process to determine the credibility of the content. Be a responsible digital citizen on social media: know when not to forward and how to express doubts.

Design of teaching activities

Activity 1: Quick classification of three short contents (10 minutes)

The teacher shows three short videos/screenshots similar to news (simulated content can be used; there is no need to spread real error information). Students work together in groups to determine:

What information is missing?

Which emotional words stimulated the discussion?

What details can be verified?

Activity 2: Stop-Check-Decision Verification Process 20 minutes

Give students a verification list:

Stop: Pause for 10 seconds and do not forward or comment immediately.

Check: What is the original source of this information?

Is there a second credible source to support?

Is there any obvious editing/out of contextence/”news description style but no source”? Decide:

Trustworthy: can be shared, but the source information needs to be provided;

Uncertain: do not forward, only save verification;

Obviously misleading: report/remind students to “lack sources” and do not spread the word.

This step naturally echoes the discovery of DAIS: due to the insufficient effect of platform labels, users need to verify the ability.

Activity 3: Role-playing comment reply 10 minutes

Scenario: A classmate forwarded a video that “looks like news” in the group. How will you respond?

Students need to write two sentences:

Polite reminder: “I’m not sure about the source. Can you provide the original link?”

A verification suggestion: “I have checked two sources, but I haven’t seen any authoritative reports yet.”

Evaluation method: 5 minutes

Each student submits a small note and answers as follows:

What is the “identification of sewage signals” I learned?

What is the first step I will take when I see similar content in the future?

Why is it necessary to use Canadian evidence to support this lesson?

MediaSmarts clearly pointed out that artificial intelligence-driven misinformation is becoming a public concern, emphasizing the need to improve critical thinking and verification habits.

DAIS research shows that small labels are unlikely to change behavior; therefore, education must make “verification and judgment” a basic skill for students, rather than relying on platform reminders.

At the same time, DAIS’s proposal to Canada’s artificial intelligence strategy also regards “skills” as a key pillar, indicating that the development of artificial intelligence/media literacy in education is in line with the policy direction.

In a word, the bad behavior of AI is not just “content deterioration”; it will change the way the public forms views and how they trust the source of information, which will also affect students’ digital citizenship. For middle school students, the most practical way is not to “memorize the concept”, but to develop a feasible habit: stop-check-decision. When verification becomes routine, the risks brought by AI become easier to manage, and opportunities are more likely to really serve learning and social participation.

Reference

MediaSmarts. (n.d.). “Wait… What?” Media Literacy Week highlights growing concern over AI-driven misinformation. https://mediasmarts.ca/about-us/press-centre/wait-what-media-literacy-week-highlights-growing-concern-over-ai-driven-misinformation

The Dais. (2025, March). Human or AI? Evaluating labels on AI-generated social media content. https://dais.ca/reports/human-or-ai/

The Dais. (2025, October). Submission to the consultation on Canada’s renewed AI strategy. https://dais.ca/reports/submission-to-the-consultation-on-canadas-renewed-ai-strategy/

My current PLN: What networks, tools and communities should I use?

At present, my PLN is mainly based on four commonly used platforms: WeChat, TikTok, Little Red Book (Little Red Book) and Bilibili.com. I don’t browse these platforms casually; on the contrary, I gradually develop my own learning process: first, I collect information from multiple sources on public platforms, then return to the private field for discussion and verification, and finally use AI to summarize and structure.

WeChat (Private Domain Polish Flower Source): I will discuss “hot topics I see” and “uncertain points” in my circle of acquaintances or groups. Common topics include social issues and policy discussions related to education, public communication and public opinion case studies, and the exchange of learning resources. The advantage of WeChat is that the trust cost is low and the feedback is fast; the disadvantage is that the information source is easily homogenized.

TikTok (trend input): I use it to observe the content of public discussion, and often read news interpretation, short comments on social issues, professional experience sharing and educational hot topics. However, I am cautious about emotional hype and misleading editing, so I usually don’t forward content easily.

Small Red Note (experience and resources): It is more like an “experience database”. I browse it for learning methods, resource collation, career preparation and education-related experience sharing. However, I also remind myself that experience posts can be clues, not evidence.

Bilibili (Systematic Learning): It is closer to the long content learning platform. I watch education/social science lectures, popular science articles on public policies and social operation mechanisms, and content related to artificial intelligence to understand how technology changes the production and dissemination of knowledge.

Career goals: Why do education-related occupations need PLN?

I hope to enter public sector positions related to education in the future (such as policy implementation, rulemaking or public communication). This means that my public learning network (PLN) can not only follow the trend, but must support three points in the long run:

Understand different stakeholders in education issues (students, teachers, parents, schools, social organizations)

Promote information from views to verifiable evidence (research, policy documents, authoritative sources)

Have public communication skills (how to explain policies, answer questions and avoid misleading)

Putting academic research together with personal experience: my contradictory attitude towards artificial intelligence is not uncommon.

The research of Estaiteyeh and Mindzak points out that prospective teachers often face a “double identity paradox”: they are both students who will use generative artificial intelligence and future teachers, and must be responsible for guiding and managing artificial intelligence; they admit that generative artificial intelligence is almost It can be avoided, but its value, use and ethical/teaching impact are still uncertain. The study also emphasizes that this is not a marginal problem, but a profound change in the teaching structure: knowledge production, evaluation and teaching practice are increasingly mediated by algorithms and artificial intelligence. Associate teachers are often worried about students’ abuse (plagiarism, superficial participation, decline in critical thinking), and also hope to learn practical strategies (using artificial intelligence to design evaluation, assist scoring and detect tool abuse).

This research is highly consistent with my experience: I mainly use artificial intelligence for learning and summary (organizing key points, structured fragmented information, and comparing views from different sources). Although it does improve efficiency, it also reminds me that taking AI output as the final answer will turn learning into “faster and more superficial understanding”. Therefore, I set a rule for myself: AI is responsible for the organization, but the key conclusions must be traced back to verifiable sources (papers, official documents, authoritative reports); otherwise, it only makes unreliable content look more “real”.

The impact of PLN + AI on fairness and accessibility

From the perspective of fairness and accessibility, AI and PLN “lower the entry threshold” and “create new barriers” at the same time:

Improve accessibility: artificial intelligence helps to understand complex information (summary, structured, language-assisted); public platforms also make information that used to circulate only in professional circles visible to a wider audience.

Create inequality: algorithm recommendations will make people fall into the echo chamber; the ability to use artificial intelligence itself may become a new digital divide; the quality of platform content varies greatly, and “accessible” is not the same as “trustworthy”.

Therefore, I think AI improves efficiency, but does not automatically improve quality. This also explains the reality of “uncertainty” and “lack of consensus framework” mentioned in the study: the system level is still adapting to change.

Critical evaluation: My advantages and disadvantages of PLN (including AI)

Advantages:

Fast input speed and wide coverage (TikTok/Xiaohongshu)

More complete input level (see Bilibili + WeChat discussion for verification for details)

Artificial intelligence helps me transform fragmented information into structured understanding (provided for follow-up verification)

Weakness:

The chain of evidence is unstable: many experience posts, the source is unknown

Eso room risk: algorithms may reinforce bias

Lack of professional community connection: at present, it is biased towards the mass platform; more opportunities to enter the education policy/teacher’s professional community are needed.

PLN in the context of Canadian education: I want to upgrade “personal browsing” to “professional network”

In the field of education in Canada, educators and educational leaders often expand their professional learning networks through online writing and public communication. Chris Kennedy’s blog “Yes Culture” (Education Leaders in West Vancouver School District) is a typical example: through continuous writing and dialogue, educational discussions are brought into the public sphere, allowing them to examine, supplement and improve views. At the same time, the Canadian Federation of Teachers (CTF) promotes the National Professional Learning and Development Network (PLDN), emphasizing the connection between provincial teacher organizations and supporting the continuous professional development of teachers.

These examples made me realize that PLN is not just “receiving information” on the platform; it can be organized, maintained for a long time, and become a part of career growth.

How can I improve PLN next:

In order to make my public education network closer to the direction of the public sector, I will do three things:

Improve information sources: pay attention to Canadian education leaders, teacher organizations, policies and research resources, rather than relying solely on algorithm recommendations.

Establish the boundaries of artificial intelligence: Artificial intelligence will be used for summary and comparison, but key conclusions must be supported by verifiable sources; do not regard artificial intelligence as authority.

Active diversification + regular review: check whether the information source is too single (language field, position, region), introduce different background voices, and insist on taking verifiable facts as the bottom line.

Reference

Estaiteyeh, M., & Mindzak, M. (2025). Building AI Literacy in Pre-Service Teacher Education in Canada.

Chris Kennedy. Culture of Yes . https://cultureofyes.ca/ Canadian Teachers’ Federation.

Professional Learning and Development Network .https://www.ctf-fce.ca/blog-perspectives/new-professional-learning-and-development-network-to-benefit-teachers-across-the-country/

Who needs to know your Professional Learning Network (PLN)?

I think my potential collaborators, colleagues, and future employers all need to know about my PLN. This is because a PLN not only represents my professional learning network, but also reflects a series of experiences, how I handle different situations, etc., all of which demonstrate my professionalism. When my future colleagues or employers understand it, I think they will have a good impression of me.

Will you continue to update your existing content and maintain your network?

Absolutely. As I just mentioned, the completeness of your PLN completely determines your image in the eyes of others. I consider it our second resume, and its value far exceeds that of a resume. It can indirectly demonstrate a person’s full range of abilities. Therefore, to save networking resources and energy, continuously building my own PLN is an excellent choice.

How do you apply your skills in professional practice?

Regarding this question, I believe I’ve found the answer through my studies. First and foremost is professional media literacy: don’t believe or spread rumors. This is fundamental. No matter what, there must be a bottom line: don’t attack, don’t smear, don’t exaggerate facts, don’t escalate situations, and always maintain a skeptical attitude towards unverified matters, considering their rationality from a fundamental perspective. Don’t believe only one side of the story; always have your own thoughts and stance. These are the skills I will use most in my Personal Network (PLN).

Personal Reflection: Before taking this course, I had no concept of a personal PLN. After taking this course, I learned about the concepts of PLN and learning networks. From a rudimentary understanding to a systematic understanding, each step has been a process of self-renewal.

Initially, I thought PLN was very simple—just a learning network, expanding one’s network of contacts, potential future colleagues and employers, etc. However, after this semester of study, I find that my views on PLN and myself have completely changed. I now believe that a Professional Network (PLN) is a springboard into the professional world. It’s like a convenient ladder, offering transparency while providing professionalism and a network of connections. It’s the best way for employers and colleagues to quickly gain a deep understanding of you. Moreover, a PLN isn’t a one-time thing; it’s an ongoing process, much like saving money. The longer you maintain it, the greater the returns, such as your past work experience and connections. Through continuous learning, I’ve realized that managing a PLN is like being a good person—like the “Magic Johnson + Michael Ovitz” example. We need to be humble, listen, observe, and learn to enrich ourselves. In short, I will continue to pursue a PLN consistently; it’s beneficial for me in every way. I enjoy collaborating with my classmates in this course and going through this learning process together, and I think we will stay in touch.

Reference:

Digital Leader: 5 Simple Keys to Success & Influence Ch. 16 Qualman, Erik – Empower Others https://learning oreilly.com.ezproxy.library.uvic.ca/library/view/digital-leader- 5/9780071792424/ 

After studying and reflecting, I wrote this post, which will answer questions such as: How can educators create discussion? What role does social media play in education? What problems exist in social media communication within an educational environment? How do Professional Learning Networks (PLNs) promote or hinder the development of ideas and concepts in education? Which social media platforms are beneficial to education? How can social media be integrated with professionalism and regulations when working with disadvantaged groups? These questions will be addressed along with my own reflections.

Harry Dale cleverly used the analogy of a stage, the two sides of a wall, and a hole in the wall to illustrate the relationship between PLN and educators, as well as PLN’s situation when facing users on different platforms. Firstly, PLN, or modern social media as commonly understood, is currently in a rather awkward position. Young people like to use social media to experience the world, but opportunities and risks coexist. Such a large-scale online platform makes it difficult to have good supervision and a highly systematic and efficient operation. Despite this, educators are constantly trying to broaden the path for future generations. For example, they are using social media platforms to spread unsolved problems and theories from ancient Europe and the Middle Ages—concepts that were merely ideas at the time—like dandelions in the wind, creating discussion and adding value and meaning to education. However, in the current environment, the resistance is still very significant. If I were to say that PLN will invest in education… In the education sector, and given its dominant position, a host of problems arise. For example, which stage of education benefits students or learners most, and which is unsuitable? Conversely, which groups are suitable and which are not? With a vast amount of information, we cannot quickly build a system like our offline learning system. First, let’s consider the simplest example: for ease of management and statistics, we categorize educational institutions below the university level by school district. This allows for resource differentiation and direct comparison. But how can we accurately achieve this comparison within a PLN (Public Learning Network)? We can’t create a “Truman Show” environment, because that would contradict our original intention—this is the first major challenge. Secondly, the second major problem is communication. Education is the transmission of information, like a spark passed down. Whether it’s a toddler learning to speak or a student like us, the process involves receiving and understanding information. But without the offline “petri dish,” how can we achieve more efficient communication? Our technology is advanced; for example, 3D projection, 5G networks, and VR can all become educational resources. However, this is a double-edged sword. Does this mean that only the wealthy are qualified to receive such modern and advanced education? If online education continues to develop in this direction, it will be a monopoly for ordinary people, a fate predetermined from birth. Therefore, how to ensure that online education maintains the same communication efficiency and results as offline education is a problem we need to consider and solve. I think fragmentation is a good idea. Since we cannot control the environment, we can segment learning according to our attention span. For example, we can use interactive methods or segmented videos to maintain communication quality. At the same time, we can establish online supervision in the education sector, combined with AI technology and large-scale model analysis to collect data. This ensures that there is no bad information or bullying during student communication, and also collects more accurate and timely data. For example, YouTube teaching videos can be broken down into smaller parts, allowing students to watch and learn repeatedly according to their needs. This is a good starting point, but it lacks supervision. Secondly, language is a thorny issue in communication. How to communicate across languages ​​is a difficult problem. I think subtitles and AI voice acting are good choices that are low-cost and efficient. However, we must return to the harsh reality that these designs are for ordinary people. Among us, there are many vulnerable groups, such as people with disabilities, autism, ADHD, and many other situations. What role does PLN education play in this regard? This is harsh. Currently, there is no way to establish effective and healthy communication among vulnerable groups because, when these sensitive and vulnerable individuals enter this new world, what they see and encounter is designed for ordinary people. When these groups join, they inevitably experience rejection and even cyberbullying. Therefore, a role similar to “cyber police” is needed to intervene. First, AI algorithms should be used to block educational videos that highlight user weaknesses. Second, users with a history of misconduct should be closely monitored to prevent them from committing violence against vulnerable groups. Rules should be established, such as the fact that bullying any other user on social media will result in a stamp appearing on one’s profile picture or in a prominent place, with a penalty lasting a week or longer to punish such behavior.

We are accustomed to traditional education, and perhaps our concepts and ideas are shackles that confine new social media education without our realizing it. We live in the 21st century, but for education, PLN feels more like it existed in the Middle Ages or even earlier, like the Renaissance, opening up a new world for society amidst controversy and resistance.

I’ve come up with a humorous analogy to describe the relationship between PLN and our current situation: modern online educational social platforms and PLN are like water bottles. They’re no longer inconvenient or unable to store water like they used to float on water. But now, all we do is use a sharp blade to cut a hole in the bottom and drink from it, not only defeating the original purpose of storing water but also causing unnecessary waste. PLN is like that—it has unlimited potential, but we educators and users need to improve ourselves to maximize its effectiveness.

Thank you for your patience in reading. If you’d like, please leave a comment so we can discuss it together!

Reference：