Many writers, actors and other creatives are currently experiencing a small wave of panic about artificial intelligence (AI) taking over their jobs.

Generative AI (GenAI) is making machine learning and creative work more accessible to everyone. But for industry professionals, the rise of generative AI can signal the destruction of creative jobs.

Yet, according to a recent report by the World Economic Forum, AI will create more jobs in the next five years than it will displace.

We are four scholars in different creative industries hoping to explore educational approaches to AI. We want to help prepare the next generation to innovate within human-AI collaborative frameworks. To do this, we have begun to confer with other creative professionals through an online survey.

What if AI can actually support human creativity and productivity? Can we use these technologies to our advantage? What we can expect for the future?

We believe creative professionals can harness new technologies while still upholding their foundational creative and ethical principles.

How AI is being used in creative sectors

AI is becoming deeply embedded within the operational workflows of creative industries, from a nascent concept to an integrated reality.

Media and creative workers have gone on strike to protest the use of AI, sparking important conversations. For example, Screenwriters in Hollywood and the Writers’ Union of Canada have raised concerns and helped shape new policies around AI and creative work.

Within media production, large language models (LLMs) can facilitate the rapid prototyping of narrative concepts, scripts and audiovisual materials, while automated editing platforms and AI-driven visual effects create massive efficiency gains in post-production. This technological integration allows creators to shift their focus from laborious manual tasks to higher-level creative refinement.

In graphic communication and packaging, AI and machine learning are acknowledged drivers of change. AI can enhance processes from ideation to production logistics like sorting and personalized web-to-print platforms. In the realm of Digital Asset Management, AI is instrumental in improving asset discoverability and utility through automated metadata tagging and sophisticated image recognition.

Journalism is also undergoing a significant transformation. AI has been used for a while now to analyze large datasets for investigative reporting, but LLMs now routinely streamline article summarization. More advanced applications are emerging: AI systems are designed to identify news values and auto-generate articles from live events. Major news organizations like the Financial Times and The New York Times are already deploying AI tools in their newsrooms.

Ethical challenges

The integration of AI is not without considerable challenges.

The generation of fabricated information and non-existent sources are documented failures. These examples highlight critical issues with accuracy and reliability.

Many people have said they do not fully understand the extent to which AI is incorporated into their standard software. This disparity between deployment and user consciousness underscores the subtle yet pervasive nature of AI’s integration. This points to an urgent need for greater transparency and digital literacy.

Bias and intellectual property

Models trained on vast, uncurated internet data often replicate and amplify existing societal biases. For example, studies demonstrate persistent issues such as anti-Muslim bias in LLMs.

At the same time, urgent ethical and legal questions regarding intellectual property have emerged. The training of LLMs on copyrighted content without compensation has created significant friction. For example, the pending New York Times litigation against OpenAI highlights unresolved issues of fair use and remuneration for creative work.

Conversely, GenAI demonstrates considerable potential to democratize creative production. These tools, by lowering technical barriers and automating complex processes, can provide access to individuals and groups historically excluded from creative fields due to resource or educational constraints.

Specific applications are already enhancing media accessibility, such as AI-powered tools that automatically generate alt text for images and subtitles for video content.

Navigating this dual-use landscape necessitates the adoption of robust governance frameworks. Fostering industry-wide equity, diversity and innovation education is essential to mitigate risks while harnessing GenAI’s potential for an inclusive creative ecosystem.

Labour and skill evolution

Technological revolutions have historically catalyzed significant transformations in creative labour markets and GenAI represents the latest disruptive force.

The proliferation of GenAI has once again reshaped the creative industries, demanding new professional competencies.

Human creativity and intervention are indispensable, providing cultural and contextual accuracy. Humans must also review AI-generated content for quality and inclusivity.

In response to this shift, higher education institutions need to recalibrate curricula from tool-specific training towards fostering curiosity, ethical reasoning and AI literacy.

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It’s become clear that many news organizations are still operating in the ethical equivalent of the Wild West when it comes to how they use artificial intelligence. (Shutterstock)

Artificial intelligence (AI) is being used in journalistic work for everything from transcribing interviews and translating articles to writing and publishing local weather, economic reports and water quality stories.

It’s even being used to identify story ideas from the minutes of municipal council meetings in cases where time-strapped reporters don’t have time to do so.

What’s lagging behind all this experimentation are the important conversations about the ethics of using these tools. This disconnect was evident when we interviewed journalists in a mix of newsrooms across Canada from July 2022 to July 2023, and it remains a problem today.

We conducted semi-structured interviews with 13 journalists from 11 Canadian newsrooms. Many of the people we spoke to told us that they had worked at multiple media organizations throughout their careers.

The key findings from our recently published research:

• AI literacy varies within the same newsroom and certainly within the industry as a whole.
• There’s agreement that humans play an important role in supervising the use of AI, but there’s no agreement on where human journalists must be involved in the process — at the AI tool coding level? Before a piece is published?
• Journalists believe professional practice and industry standards are being followed when using AI in journalism, but there is no agreed-upon “rule book” for how AI should be used.
• There are issues with transparency about how and when AI is being used, both among journalists working in the same newsroom and in terms of what is revealed to audiences about whether the content they are consuming was created using AI tools.

What journalists told us

Some of what we heard was reassuring. One journalist told us:

“The one thing that we are very particular about when we use this technology is that our editors always have the ability to override what the machine is doing.”

At the same time, however, it became clear that many news organizations are still operating in the ethical equivalent of the Wild West.

In many cases, journalists we spoke to talked about just following their gut when it came to deciding if using that AI tool to do that task was ethical. As one of our interviewees put it: “There’s a rule book in my head.”

When we asked interviewees how they knew their colleagues at the same publication followed the same ethical code they did when using AI, most could not answer except to imply that their co-workers wouldn’t have been hired if they didn’t share the same principles. One journalist said:

“I’ve worked there for 14 years now …I can’t think of anyone whose ethics I would disagree with.”

Getting the ethics of AI right and being seen to be doing so is important because journalism has a growing trust problem and needs to do everything possible to reverse the trend.

Multiple studies have shown that Canadian audiences want to know if AI tools are being used in newsrooms, and they aren’t sure if they want to pay for journalism created using AI.

AI and news

Audiences, meanwhile, are being fed a steady diet of examples that illustrate how using AI tools to create journalistic work can go very wrong. For instance:

• The Winnipeg Free Press was forced to disavow its AI audio tool because it was mispronouncing the Manitoba premier’s name.
• An article in the Los Angeles Times was accused of “softening the image of the Ku Klux Klan.”
• An AI-generated poll about a report in The Guardian provoked outrage when it quizzed readers on how a woman who was featured in the article had died. The poll was created by a Microsoft news aggregator, but The Guardian stated that it damaged their reputation.
• Sports Illustrated was caught creating fake bylines for AI-generated stories on their websites.

News organizations might think they’re being transparent with audiences about how much content is being created using AI, but our research finds the evidence is mixed at best, especially in circumstances where AI generates the content and an editor approves it in the content management system before it is published.

In one memorable Zoom interview, an editor walked us through the AI-generated content in an article posted online, saying that it was clearly identified as AI on the webpage.

However, upon sharing the page, they were shocked to discover there was no information about the article being AI-generated anywhere. They said it would be fixed immediately, but when we last checked, the article still said nothing about the AI tool used to generate it.

While we gathered data from interviews, newsrooms in Canada started releasing guidance through internal emails and public blog posts. It is hard to find any language in publicly accessible policies that refers explicitly to how AI is being used or the ethics surrounding such use. It’s also unclear who is involved in conversations about ethical AI use in newsrooms, and who is not.

As one journalist we interviewed put it:

“I think my frustration personally comes from again the lack of openness to have this conversation about AI, and the urgency of it, because I think … we’re so busy trying to survive, we don’t realize that having this conversation about AI will help us survive.”

Our research suggests journalists and news organizations are still struggling in the midst of rapid technological change to arrive at a shared understanding of AI tools, their usage, the limitations of programming and best practices that build rather than erode trust.

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Canadians need literacy around AI, its applications and uses. (Shutterstock)

When ChatGPT entered the public imagination in 2022, Canadians were curious, hopeful, anxious and had plenty of questions. Just three years later, our new report, The State of Generative AI Use in Canada 2025, finds that two-thirds of Canadians have already experimented with generative AI (GenAI) tools.

That is an astonishing rate of adoption for a technology so novel, and it speaks to the profound impact it’s already having on our lives.

But alongside this rapid uptake is a sobering reality: most Canadians are still unsure about what these tools are, how they work or how they affect society. Our new national survey of 1,500 adults, conducted in February and March, reveals that while GenAI use is widespread, deep understanding is not.

Canadians are being ushered into a new era of AI-powered productivity, creativity and communication. But they are forging ahead without the digital literacy needed to navigate AI technologies and their impacts effectively, safely and critically.

News and politics

Only 38 per cent of respondents indicated they felt confident using these tools effectively. Even fewer — 36 per cent — told us they were familiar with the rules and ethics around GenAI. These numbers should concern all of us.

Nowhere is this tension clearer than in how Canadians view GenAI’s impact on information, media and politics. Canadians’ comfort levels with GenAI use in newsrooms vary sharply depending on the topic: people are relatively at ease with AI-generated content in entertainment and lifestyle reporting, but not as much with more sensitive topics such as politics, crime or global affairs.

Our survey also reveals that two‑thirds (67 per cent) worry GenAI could be used to manipulate voters or interfere with democratic processes. At the same time, trust in political information online is eroding, with 59 per cent saying they no longer trust the political news they see online due to concerns that it may be fake or manipulated.

Although GenAI tools like chatbots could help voters assess policies proposed by different parties and their potential implications, most Canadians (54 per cent) are unlikely to use them to get information about elections or politics.

Responsible innovation

So what are Canadians asking for? More than anything, our findings show overwhelming support for regulatory guardrails. Canadians want clear rules for companies that develop, use or provide GenAI-powered tools and services.

Seventy-eight per cent of Canadians say GenAI companies should be held accountable when their tools cause harm. Nearly eight in 10 also support both the regulation of current state-of-the-art GenAI tools and the proactive regulation of GenAI tools on the horizon.

This is a call for leadership and action. Canada has the chance to set a global standard for responsible AI governance, but must act quickly and decisively. We offer three core recommendations to help chart that path:

1. Policy leadership: Considering the ongoing race among GenAI companies to build the most advanced model, the principles of privacy by design should not be sacrificed simply to gather more user data. The risks associated with data breaches and accidental leaks of personal information in GenAI outputs are significant.

This means prompts and other user inputs should not be used for fine-tuning or training future models without obtaining meaningful consent first. Furthermore, to address Canadians’ concerns about how GenAI companies manage personal information, the Office of the Privacy Commissioner of Canada should take stock of popular GenAI tools and proactively review their privacy and data use policies to ensure compliance with existing privacy regulations.

2. Education reform: Given the relatively low level of GenAI literacy among Canadians, integrating GenAI — and AI literacy more broadly — into the education system is essential. From K-12 through post-secondary, students must learn not just how to use GenAI tools effectively (for example, prompt engineering). They should also understand how these technologies function, where the training data come from and how to evaluate outputs for accuracy and potential biases.

3. GenAI use transparency: Organizations deploying GenAI must clearly disclose when and how these tools are being used, alongside mandatory risk assessments for high-impact deployments. This transparency is particularly important for for-profits, media outlets and public sector entities, as these groups are viewed with the highest levels of distrust among Canadians regarding the safe and ethical use of GenAI.

Dizzying change

As researchers who have spent years studying technology’s impact on society, we are both excited and cautious about what GenAI means for Canada. The pace of change is dizzying, but speed alone is not a measure of progress. What matters is whether this technology serves the public good.

Canadians are not anti-technology. They are curious, pragmatic and hopeful, but they are also alert to the risks. They want to be part of the conversation, and they want to see that conversation lead to thoughtful, inclusive action.

We urge policymakers, educators, tech companies and civil society to listen closely and act urgently. GenAI is not a passing trend. It is reshaping how we work, learn and spend leisure time. Whether that transformation uplifts or undermines society depends on our current choices.

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When it comes to artificial intelligence (AI) and news production, Canadian news consumers want to know when, how and why AI is part of journalistic work. And if they don’t get that transparency, they could lose trust in news organizations.

News consumers are so concerned about how the use of AI could impact the accuracy of stories and the spread of misinformation, a majority favour government regulation of how AI is used in journalism.

These are some of our preliminary findings after surveying a representative sample of 1,042 Canadian news consumers, most of whom accessed news daily.

This research is part of the Global Journalism Innovation Lab which researches new approaches to journalism. Those of us on the team at Toronto Metropolitan University are particularly interested in looking at news from an audience perspective in order to develop strategies for best practice.

The industry has high hopes that the use of AI could lead to better journalism, but there is still a lot of work to be done in terms of figuring out how to use it ethically.

Not everyone, for example, is sure the promise of time saved on tasks that AI can do faster will actually translate into more time for better reporting.

We hope our research will help newsrooms understand audience priorities as they develop standards of practice surrounding AI, and prevent further erosion of trust in journalism.

AI and transparency

We found that a lack of transparency could have serious consequences for news outlets that use AI. Almost 60 per cent of those surveyed said they would lose trust in a news organization if they found out a story was generated by AI that they thought was written by a human, something also reflected in international studies.

The overwhelming majority of respondents in our study, more than 85 per cent, want newsrooms to be transparent about how AI is being used. Three quarters want that to include labelling of content created by AI. And more than 70 per cent want the government to regulate the use of AI by news outlets.

Organizations like Trusting News, which helps journalists build trust with audiences, now offer advice on what AI transparency should look like and say it’s more than just labelling a story — people want to know why news organizations are using AI.

Audience trust

Our survey also showed a significant contrast in confidence in news depending on the level of AI used. For example, more than half of respondents said they had high to very high trust in news produced just by humans. However, that level of trust dropped incrementally the more AI was involved in the process, to just over 10 per cent for news content that was generated by AI only.

In questions where news consumers had to choose a preference between humans and AI to make journalistic decisions, humans were far preferred. For example, more than 70 per cent of respondents felt humans were better at determining what was newsworthy, compared to less than six per cent who felt AI would have better news judgement. Eighty-six per cent of respondents felt humans should always be part of the journalistic process.

As newsrooms struggle to retain fractured audiences with fewer resources, the use of AI also has to be considered in terms of the value of the products they’re creating. More than half of our survey respondents perceived news produced mostly by AI with some human oversight as less worth paying for, which isn’t encouraging considering the existing reluctance to pay for news in Canada.

This result echoes a recent Reuters study, where an average of 41 per cent of people across six countries saw less value in AI-generated news.

Concerns about accuracy

In terms of negative impacts of AI in a newsroom, about 70 per cent of respondents were concerned about accuracy in news stories and job losses for journalists. Two-thirds of respondents felt the use of AI might lead to reduced exposure to a variety of information. An increased spread of mis- and disinformation, something recognized widely as a serious threat to democracy, was of concern for 78 per cent of news consumers.

Using AI to replace journalists was what made respondents most uncomfortable, and there was also less comfort with using it for editorial functions such as writing articles and deciding what stories to develop in the first place.

There was far more comfort with using it for non-editorial tasks such as transcription and copy editing, echoing findings in previous research in Canada and other markets.

We also gathered a lot of data unrelated to AI to get a sense of how Canadians are tapping into news and the news they’re tapping into. Politics and local news were the two most popular types of news, chosen by 67 per cent of respondents, even though there is less local news to consume due to extensive cuts, mergers and closures.

A lot of people in our sample of Canadians, around 30 per cent, don’t actively look for news. They let it find them, something called passive consumption. And although this is proportionally higher in news consumers under 35, this isn’t just a phenomenon seen in the younger demographic. More than half of those who reported letting news find them were over 35 years old.

Although smartphones are increasingly becoming the likely access points of news for many consumers, including almost 70 per cent for those 34 and under and about 60 per cent of those between 35 and 44, television is where most news consumers in our study reported getting their journalism.

Respondents in our survey were asked to select all of their points of news access. More than 80 per cent of participants chose some form of TV, with some respondents picking two TV formats, for example, cable TV and smart TV. Surprisingly to us, half of 18-24 year olds reported TV as an access point for news. For those 44 and under, it was more often through a smart TV, though. As shown in other Canadian studies, TV news still plays an important role in the media landscape.

This is just a broad look at the data we have collected. Our analysis is just beginning. We’re going to dig deeper into how different demographics feel about the use of AI in journalism and how the use of AI might impact audience trust.

We will also soon be launching our survey with research partners in the United Kingdom and Australia to find out if there are differences in perceptions of AI in the three countries.

Even these initial results provide a lot of evidence that, as newsrooms work to survive in a destabilized market, using AI could have detrimental effects on the perceived value of their journalism. Developing clear policies and principles that are communicated with audiences should be an essential part of any newsroom’s AI practice in Canada.

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Written by Omar H. Fares, Toronto Metropolitan University. Originally published in The Conversation. 

An advertisement for Google Gemini sparked widespread backlash online about the growing role of generative AI tools and their impact on human creativity, productivity and communication. (Shutterstock) 

After widespread backlash, Google pulled its “Dear Sydney” Gemini ad from Olympics coverage. The ad featured its generative AI chatbot tool, Gemini, formerly known as Bard.

The advertisement featured a father and his daughter, a fan of United States Olympic track and field athlete Sydney McLaughlin-Levrone. The father, despite considering himself “pretty good with words,” uses Gemini to help his daughter to write a fan letter to Sydney, saying that when something needs to be done “just right,” Gemini is the better choice.

This advertisement sparked widespread backlash online about the growing role of generative AI tools and their impact on human creativity, productivity and communication. As media professor Shelly Palmer wrote in a blog post:

“As more and more people rely on AI to generate their content, it is easy to imagine a future where the richness of human language and culture erode.”

Critics argue that relying on AI for tasks traditionally done by humans will undermine the value of human effort and originality, leading to a future where machine-generated content overshadows human output.

The controversy brings up key questions about the preservation of human skills, and the ethical and social implications of integrating generative AI tools into everyday tasks. The question here is where the line should be drawn between AI and human involvement in content creation, and whether such a dividing line is necessary at all.

Anthropomorphic AI

AI tools are effectively integrated in almost all aspects of our daily activities, from entertainment to financial services.

Over the past few years, generative AI has appeared to become more contextually aware and anthropomorphic, meaning its responses and behaviour are more human-like. This has led more people to integrate the technology into their daily activities and workflows.

Many people, however, are struggling to strike a balance when it comes to using these tools. On the one hand, given enough human oversight, advanced models of ChatGPT and Gemini can deliver cohesive, relevant responses. In addition, the pressure to use these tools is strong, and some people fear that not using them will set them back professionally.

But, on the other hand, AI-generated content lacks a unique, human touch. Even as prompts improve, there remains a generic quality to AI responses.

To better understand the implications of AI-generated content on human communication, and the issues that stem from them, it’s important to adopt a balanced approach that avoids both uncritical optimism and pessimism. The elaboration likelihood model of persuasion can help us achieve this.

The nature of persuasion

The elaboration likelihood model of persuasion suggests there are two routes of persuasion: the central route and the peripheral route.

When individuals process information through the central route, they engage in thoughtful and critical evaluation of information. In contrast, the peripheral route involves a superficial assessment based on external cues, rather than the content’s quality or relevance.

In the context of AI-generated content, there is a risk that both creators and recipients will increasingly rely on the peripheral route. For creators, using AI tools might reduce the effort invested in crafting messages, knowing that the technology will handle the details.

For recipients, the polished nature of AI-generated content might lead to a surface-level engagement without deeper consideration. This superficial engagement could result in the undermining of the quality of communication and the authenticity of human connections.

This phenomenon is particularly evident in hiring. Generative AI tools can produce cover letters based on job descriptions and resumes, but they often lack the personal touch and genuine passion that human-crafted letters might convey.

As hiring managers receive an increasing number of AI-generated applications, they are finding it difficult to uncover the true capabilities and motivations of candidates, which is resulting in less-informed hiring decisions.

Where do we go from here?

This leaves us at a crossroad. While arguments can be made for the effective integration of AI with human oversight, there is also a significant concern that the perceived value of messages and our communication is diminishing.

It is increasingly apparent that AI tools are here to stay. Our collective line of inquiry needs to shift towards exploring a state of interdependence, where society can maximize the benefits of these tools while maintaining human autonomy and creativity.

Achieving this balance is challenging and begins with education that emphasizes foundational human capabilities such as writing, reading and critical thinking. Additionally, there should be a focus on developing subject matter expertise to help individuals to better use these tools and extract maximum value.

Clarifying the limits of AI integration is equally important. This may involve avoiding AI usage in personal communication, while accepting its role in organizational public communication, such as industry reports where AI can enhance readability and quality.

It is of timely essence to understand that our collective societal decisions will have significant future impacts. This moment calls for fellow researchers to deepen the exploration of the interdependence between humans and AI, allowing technology to be used in ways that complement and enhance human capabilities, rather than replace them.

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Five Ontario school boards are suing the companies behind major social media platforms Facebook, Instagram, Snapchat and TikTok, alleging their addictive products have caused the students to suffer from mental health issues, and causing widespread damage and disruption to the education system.

Recently, five school boards in Ontario filed a lawsuit against the major social media platforms: Facebook and Instagram, Snapchat and TikTok.

Their lawsuit says that these platforms are designed to be addictive and have caused all kinds of problems for the education system. The lawsuit says social media causes children to suffer from mental health issues, and it increases distraction, social withdrawal, and cyberbullying. And it causes damage and disruption to the classroom, putting all kinds of new burdens on teachers who are already dealing with shrinking budgets and increased class sizes.

The $4.5 billion lawsuit follows over 200 lawsuits by school boards in the United States in the past year against the same companies, making similar claims.

This week, the Ontario government, which has called the Canadian lawsuit a waste of time and money, announced it was doubling down on its 2019 ban on cellphones in schools as a way to address the problem.

But is a ban the answer to the impact of technology we know is incredibly pervasive, addictive and harmful? Not to mention, often racist?

Research shows technologies are not neutral: They’re embedded with and actively reinforce structures of racism. A survey of Canadian children in grades 7 to 11 found nearly half of participants reported seeing racist or sexist content online, and youth from marginalized groups were more likely than others to encounter this type of content. So, what’s to be done?

On this week’s Don’t Call Me Resilient podcast, our guests are two scholars and former teachers who look at the intersection of race, technology and education. They say social media has become part of who we are and it’s not going anywhere.

Instead of trying to ban it and monitoring students to make sure they adhere to the ban, schools should focus on improving digital media literacy and critical thinking — for students and their teachers.

Beyhan Farhadi is Assistant Professor of Educational Policy and Equity at the Ontario Institute for Studies in Education, University of Toronto and Kisha McPherson is an Assistant Professor in the School of Professional Communication at Toronto Metropolitan University.

“How can we effectively use [the cellphone] within the classroom? It could be a research tool… it could be a pedagogical tool to teach and to do different things. With the money that is put towards these surveillance measures and put towards these forms of punitive decisions…it really begs the question of whether or not we’re really concerned about students or are we just finding ways to maintain a status quo of control….” – Kisha McPherson, Assistant Professor, Toronto Metropolitan University

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Sora could serve as a tool that enhances the capabilities of content creators, allowing them to produce higher-quality content more efficiently. (Shutterstock)

OpenAI’s new generative Sora tool has sparked lively technology discussions over the past week, generating both enthusiasm and concern among fans and critics.

Sora is a text-to-video model that significantly advances the integration of deep learning, natural language processing and computer vision to transform textual prompts into detailed and coherent life-like video content.

In contrast to previous text-to-video technologies, like Meta’s Make-A-Video, Sora is able to overcome limitations related to the type of visual data it can interpret, video length and resolution.

From what OpenAI has demonstrated, Sora can generate videos of various lengths, from short clips to full-minute narratives, and in high definition, accommodating a wide range of creative needs.

Although no official release date has been announced, Sora will likely be available to the public in the coming months, judging by OpenAI’s typical pattern of public releases. For now, it’s only available to experts and a few artists and filmmakers.

How Sora works

At the heart of Sora’s innovation is a technique that transforms visual data into a format it can easily understand and manipulate, similar to how words are broken down into tokens for AI processing by text-based applications.

This process involves compressing video data into a more manageable form and breaking it down into patches or segments. These segments act like building blocks that Sora can rearrange to create new videos.

Sora uses a combination of deep learning, natural language processing and computer vision to achieve its capabilities.

Deep learning helps it understand and generate complex patterns in data, natural language processing interprets text prompts to create videos, and computer vision allows it to understand and generate visual content accurately.

Introducing Sora, our text-to-video model.

Sora can create videos of up to 60 seconds featuring highly detailed scenes, complex camera motion, and multiple characters with vibrant emotions. https://t.co/7j2JN27M3W

Prompt: “Beautiful, snowy… pic.twitter.com/ruTEWn87vf

— OpenAI (@OpenAI) February 15, 2024

By employing a diffusion model — a type of model that’s particularly good at generating high-quality images and videos — Sora can take noisy, incomplete data and transform it into clear, coherent video content.

Sora’s approach differs from CGI character creation, which requires extensive manual effort, and from traditional deepfake technologies, which often lack ethical safeguards, by offering a scalable and adaptable method for generating video content based on textual input.

What does this mean for businesses?

One of the most noteworthy aspects of Sora is its flexibility, as it supports various video formats and sizes, enhances framing and composition for a professional finish, and accepts text, images or videos as prompts for animating images or extending videos.

The emergence of Sora presents key opportunities for businesses across different sectors. In the near future, there are two key areas that may have significant applications.

The first area is in marketing and advertising. Just as ChatGPT has become a marketing and content creation tool, we can expect businesses to use Sora for similar reasons.

With the public release of Sora, brands and companies will be able to create highly engaging and visually appealing video content for marketing campaigns, social media and advertisements.

The ability to generate custom videos based on textual prompts will allow for greater creativity and personalization, possibly helping brands stand out in a crowded market.

https://www.youtube.com/watch?v=5JiN_OARcuo&embeds_referring_euri=https%3A%2F%2Ftheconversation.com%2F&source_ve_path=MjM4NTE&feature=emb_title

The second area Sora could impact is training and education. Companies could use Sora to develop educational and training videos that are tailored to specific topics or scenarios. This could enhance the learning experience for employees and customers, making complex information more accessible and engaging.

Other sectors, such as e-commerce, also hold promising potential for the future application of Sora. Retailers could create dynamic product demonstrations that effectively showcase products in a more engaging and interactive manner.

This would be especially beneficial for companies that want to highlight specific aspects of products that might not be easily conveyed through static images or text, or for advertising products that require a detailed explanation.

Sora could also significantly reduce the uncertainty associated with online shopping by facilitating virtual try-on experiences, allowing customers to visualize how a product, such as clothing or accessories, would look on them without the need for a physical fitting. This, in turn, could result in a better return on investment.

What are the key challenges ahead?

While there are key opportunities ahead, OpenAI, regulators and users need to carefully consider key factors that could pose challenges, including copyright issues, ethical concerns and the consequences of increased digital noise.

With Sora’s ability to generate lifelike video content, there’s a risk of inadvertently creating videos that infringe on existing copyrights. OpenAI has already been sued several times over copyright infringement and intellectual property issues.

OpenAI hasn’t disclosed where the data used to train Sora is from, but it did tell the New York Times it was training the system using videos that were publicly available and licensed from copyright holders.

The technology also raises ethical questions, particularly around the creation of deepfake videos or misleading content.

Establishing guidelines and safeguards to prevent misuse will be essential for maintaining trust in the technology. In a post on its website, OpenAI stated it was working with experts to test the model before releasing it to the public.

As more businesses and individuals gain access to Sora, there’s a potential for an increase in low-quality or irrelevant video content, leading to increased “digital noise” that could overwhelm users. Finding ways to filter and curate content will become increasingly important for businesses looking to maintain their edge.

Last, but certainly not least, is the question of how Sora will impact the job market for content creators. While Sora does have the potential to automate certain aspects of video production, like ChatGPT, it’s unlikely to replace human creativity and insight anytime soon.

Instead, Sora could serve as a tool that enhances the capabilities of content creators, allowing them to produce higher-quality content more efficiently. As with any technological advancement, the key will be for professionals to adapt and find ways to integrate Sora into their workflows, leveraging its strengths to complement their own skills and creativity.

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Neuralink is developing devices that enable direct communication between the human brain and computers. (Shutterstock)

The first human has received a Neuralink brain chip implant, according to co-founder Elon Musk. The neurotechnology company has started its first human trial since receiving approval from the U.S. Food and Drug Administration in 2023.

The trial’s focus is on an implant that could potentially allow people with severe physical disabilities to control digital devices using their thoughts. The study involves implanting a brain chip — called a brain-computer interface implant — in the region of the brain that controls movement intention.

Musk has said the patient who received the implant — fittingly named Telepathy — is “recovering well” and that “initial results show promising neuron spike detection.” No other details about the trial have been provided yet.

The first human received an implant from @Neuralink yesterday and is recovering well.

Initial results show promising neuron spike detection.

— Elon Musk (@elonmusk) January 29, 2024

This development is more than just a technical milestone; it represents a major leap in potential human-computer interaction, raising important questions about the integration of advanced technology with the human body and mind.

Neuralink’s mission

Neuralink’s stated mission is to “create a generalized brain interface to restore autonomy to those with unmet medical needs today and unlock human potential tomorrow.” This mission communicates two key approaches.

In the short term, the focus will be on individuals with medical needs. The long-term vision extends far beyond this, alluding to a goal of augmenting human potential. This suggests Neuralink envisions a future where its technology transcends medical use and becomes a tool for cognitive and sensory enhancement in the general population.

The evolution of Neuralink presents a range of possible future scenarios. The first scenario envisions successful trials leading to adoption in niche markets, signifying a breakthrough but with restricted scope.

The second, more optimistic scenario, involves widespread acceptance after successful human trials, with the potential to revolutionize our interaction with technology. And the third — a more pessimistic view — considers the venture’s failure, driven by many societal, technological, legal and medical factors.

The realistic scenario

In the most realistic scenario, Neuralink is expected to achieve success by focusing on medical applications for individuals with severe disabilities. This targeted approach is likely to resonate with consumers in need of life-changing technologies, which will drive early adoption within this specific demographic.

In this case, wider acceptance from the broader consumer base will hinge on various factors, including the technology’s perceived usefulness, privacy implications and the overall risk-benefit perception.

Socially, Neuralink’s trajectory will be significantly influenced by public and ethical discussions. Issues surrounding data security, long-term health implications and equitable access will likely dominate public discourse.

Widespread acceptance of Neuralink’s technology will depend on its medical efficacy and safety, combined with Neuralink’s ability to address ethical concerns and gain public trust.

The optimistic scenario

In the optimistic scenario, Neuralink’s technology transcends its initial medical applications and integrates into everyday life. This scenario envisions a future where the technology’s benefits are clearly demonstrated and recognized beyond its medical use, generating interest across various sectors of society.

Consumer interest in Neuralink would extend beyond those with medical needs, driven by the appeal of enhanced cognitive abilities and sensory experiences. As people become more familiar with the technology, concerns about invasiveness and data privacy may decrease, especially if Neuralink can provide robust safety and security assurances.

From a societal standpoint, the optimistic scenario sees Neuralink as a catalyst for positive change. The technology could bridge gaps in human potential, offering new ways of interaction and communication.

Although ethical concerns would still exist, the potential benefits in education, workforce productivity and overall quality of life could outweigh them. Regulatory bodies might adopt more accommodating policies, influenced by public enthusiasm and the technology’s track record in improving lives.

In this scenario, Neuralink becomes a symbol of human advancement, seamlessly integrating into daily life and opening new possibilities in human-machine interaction.

Its success would set a precedent for other technologies at the intersection of biology and technology, like gene editing technologies  and bioelectronic medicine, paving the way for a future where such integrations are the norm.

The pessimistic scenario

In the pessimistic scenario, Neuralink will face significant challenges that hinder its widespread adoption and success. This scenario considers the possibility of the technology failing to meet the high expectations set for it, either due to technological limitations, safety concerns or ethical dilemmas.

From a technological standpoint, the complexity of interfacing directly with the human brain could be more complex than anticipated, leading to underwhelming performance or reliability issues.

Physical and psychological safety concerns might also be more significant than initially thought, with potential long-term health implications that could deter both consumers and medical professionals.

The invasive nature of the technology and privacy concerns related to brain data could lead to widespread public apprehension. This skepticism could be compounded if early applications of the technology are perceived as benefiting only a select few, exacerbating social inequalities.

Ethically, the prospect of brain-computer interfaces could raise questions about human identity, autonomy and the nature of consciousness. These concerns might fuel public opposition, leading to stringent regulatory restrictions and slowing down research and development.

In this scenario, Neuralink’s ambitious vision might be curtailed by a combination of technological hurdles, public mistrust, ethical controversies and regulatory challenges, ultimately leading to the project’s stagnation or decline.

While Neuralink presents numerous possibilities, its journey isn’t merely about technological advancement. The outcome of this venture holds key implications for the future of neural interfaces and our understanding of human capabilities, underscoring the need for a thoughtful approach to such innovation.

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Canada should invest in sustainable transportation infrastructure to accelerate the green transition.

The green transition is happening too slowly. We are in a climate emergency, and it is clear that we need to reduce greenhouse gas emissions by transitioning to more sustainable transportation.

However, without sufficient infrastructure to enable electric vehicles (EVs) or cycling for commuting, these options will remain too inconvenient or unsafe for most. Canada’s climate obligations will not be met without these infrastructure changes.

We just experienced the hottest July on record. We cannot burn more carbon, no matter the remaining carbon budget. Climate disasters around the world today are dictating timelines now. Meanwhile, gas cars are needlessly on city streets, adding to traffic congestion and pollution while urban sprawl means gas car driving habits expand.

Canada requires urgent investment in transport infrastructure and incentives to reverse this trend.

Policy breakdowns

Here in Toronto, a recent mayoral election provided a platform for two candidates who made election promises to close down cycling lanes. Meanwhile, a lack of high-quality cycling infrastructure in the city incentivizes travel by car to the detriment of the city’s happiness and carbon budget.

This stands in stark contrast to a city like Copenhagen, Denmark where 62 per cent of people commute by cycling. A city which, by some metrics, may also be the happiest in the world.

Canada currently has both a lack of cycling infrastructure and reliable bike storage options. Photo credit: THE CANADIAN PRESS/Justin Tang

Closer to home, cycling infrastructure remains poor and bike theft rose by 429 per cent in Canada this summer. However, the solutions to this problem, such as bicycle lockers, are not widely enough installed and where they do exist, they are only for regular users and require a reservation and monthly payments.

Solutions such as an on-demand bicycle storage system being piloted in Vancouver and the Vancouver City Centre Bike Valet show promise for nation-wide implementation but will require effort to implement at scale.

Nowhere to charge

Likewise, a recent survey says that Canadians are not switching to cleaner EVs partly because of a lack of charging infrastructure. In a climate emergency, bike and electric vehicle infrastructure should have been installed long ago.

Toronto’s mandate is to reach net zero by 2040, but its efforts pale in comparison to the actions of other cities in Canada and around the world.

A variety of incentives and legislation are accelerating an EV transition including fee exemptions, grants and mandated targets. Brazil is proposing that all gas stations offer EV charging.

A lack of enthusiasm for EVs in Canada is driven largely by a lack of reliable charging infrastructure. Photo credit: THE CANADIAN PRESS/Adrian Wyld

Ireland’s zero emissions office is aiming for 100 per cent of new car sales to be EVs by 2030. France supports EV purchases with funding and bonuses for low income individuals. Ecuador’s public transport will be 100 per cent electric by 2025 and Sweden’s government fleet will be electrified by 2035. Colombia and South Africa are setting EV charging infrastructure minimums.

There are notable Canadian EV initiatives in Québec and British Columbia. Québec has ambitious electrification plans including expanding EV charging, funding further vehicle electrification across the province. B.C. is improving upon the Canadian national mandate by installing more EV charging stations and planning a changeover to clean vehicles.

In contrast, Ontario and Toronto are without any unique innovations in electric vehicle infrastructure or policy.

An electric future

EVs are already addressing local air pollution around the world and reducing health issues such as asthma. Higher EV sales are also associated with higher human development indexes (HDI). An HDI is a national measure of wealth, and a good reflection of standard of living, including health and education. Countries with higher EV sales also tend to lead worldwide in the development of environmental inventions. Healthier inventions make a better life.

Perhaps in Sweden, France, The Netherlands, Germany, Japan, Norway and certain Canadian provinces such as Québec and B.C., the connection is clearer between switching to cleaner technologies and increasing levels of personal health and happiness. Improving education is a catalyst for change.

An example of an electric charging station designed around a familiar gas pump form factor. Photo credit: THE CANADIAN PRESS/Doug Ives

If Canada is to meet its climate commitments, it has to drastically reduce greenhouse gas emissions from transportation. Infrastructure investments, such as for EVs and cycling, improve our quality of life and the economy at the same time. Building infrastructure is a classic approach to boosting an economy. It is also a green economic opportunity if the right choices are made.

Canada can start by applying well-known policy solutions and rapidly installing infrastructure nationwide. Studies have validated this recommendation and additional phased-in electrical grid capacity is neither controversial nor impractical. Emissions reductions with EVs as compared to gas cars, no matter the energy fuel source, ultimately validate EVs green utility over gas-powered cars.

Around the world, such as in China where they have energy mix variations across regions including coal, EVs make sense. Emissions reductions for Ontario have been calculated at around 80 per cent when EVs are driven.

The International Energy Agency offers a comprehensive policy database of worldwide examples for places like Toronto that are lagging on clean transportation transition policy and change. Beyond benchmarking, Canada could strive for leadership on the world stage by investing in university research and applying ambitious initiatives across the country.

Canada has an opportunity that should not be missed to stimulate its economy by investing in sustainable transportation infrastructure to accelerate the green transition.

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Instead of owning physical copies of DVDs or CDs, for example, people subscribe to streaming services, allowing them to access a wide range of products without the burden of traditional ownership.

Today’s consumer landscape is witnessing a pivotal shift away from traditional ownership towards an access-based model. Rather than outright owning goods and services, people prefer to simply have access to them.

Access-based consumption means engaging in transactions where ownership doesn’t change hands. Instead of owning physical copies of DVDs or CDs, for example, people subscribe to streaming services. Consumers are able to access a wide range of products without the burden that comes with traditional ownership.

This approach is closely associated with the sharing economy, which encourages collaborative consumption. This involves sharing, swapping and renting resources, eliminating the need for personal ownership of these goods.

The term “sharing economy” came into use after the 2007 financial crisis as people sought alternative ways to access goods and services, but started gaining more widespread usage in 2010 and 2011.

The sharing economy is growing exponentially. It’s projected to reach a market volume of $335 billion by 2025. This indicates that the way we consume goods and services has — and continues to — evolve significantly.

A response to global challenges

At a time filled with economic instability driven by a wealth of factors, including the long-lasting effects of COVID-19 and the war in Ukraine, consumers continue to shift their consumption habits to align with these economic shocks.

The access-based and sharing economy has emerged as a powerful response to these global challenges, offering a flexible, cost-effective and more sustainable alternative to the long-standing paradigm of ownership.

The rise of access-based consumption doesn’t appear to be a passing phase. Rather, it appears to be an enduring form of consumption that is emerging in various industries, including transportation, fashion and toys.

Navigating the current economic landscape requires a solid grasp of these evolving paradigms. The rise of the access-based and sharing economy is more than a trend towards cost saving; it’s about constructing a sturdier, sustainable consumption model.

What is driving the shift

The growth of access-based consumption is driven by two main things. First, access-based consumption is predicated on the affordability, value and convenience it offers to consumers. Participation in car-sharing services, such as Zipcar and Turo, are primarily driven by these factors.

Secondly, access-based consumption provides environmental and social benefits by encouraging consumers to share and increasing the usage of a particular good.

In the fashion industry, rental services allow consumers to enjoy a variety of choices and gain access to luxury goods they may not otherwise be able to purchase. These services are also beneficial for those experiencing body changes, like pregnant women, as clothing can be shared to reduce careless disposal.

Access-based consumption means there is a time-related aspect to the transaction, either in the form of duration of access or usage. Even so, this doesn’t stop consumers from developing a sense of perceived ownership over a good or service.

For example, consumers may develop a sense of pride, attachment and responsibility towards a shared community garden. They may gain social value from participating in this experience.

This social component also extends to peer-to-peer accommodation services, like Airbnb. One study found that the primary reasons American travellers used such a service included sustainability and connecting with community.

Interestingly, while service providers tout intrinsic motivations, such as promoting sustainability and building a community, users often have extrinsic factors such as affordability and convenience on top of their minds.

What does this mean for businesses?

Businesses need to reimagine traditional profit strategies, resource utilization, societal impacts and community relationships to better adapt to this shift in the economic paradigm.

Rethink profit: In an access-based economy, businesses need to shift their profit strategies from selling products to facilitating access. This calls for innovative approaches to monetizing services, such as tiered subscriptions, dynamic pricing or pay-per-use approaches, creating multiple revenue streams while fulfilling diverse consumer needs.

Maximizing technological resources: The role of technology is central in orchestrating transactions, maintaining inventory and ensuring a seamless user experience. In an access-based environment, businesses must harness tech advancements like AI, data analytics and the Internet of Things to streamline operations. Investing in digital infrastructure is critical to success in the access-based economy.

Beyond revenue: Profit isn’t the sole aim anymore. The access-based economy focuses on sustainable practices and societal impact. Businesses can position themselves as conscious brands by promoting resource optimization and contributing to societal and communal welfare. This shift towards corporate social responsibility not only elevates a brand’s image, but also resonates with the growing consumer demand for ethical consumption.

The power of trust: Trust is one of the cornerstones of the access-based economy. Consumers need the assurance of safety, quality and reliability before partaking in sharing transactions. Businesses can foster trust by implementing transparent practices, rigorous quality checks and responsive customer service.

The future of consumerism

While ownership does offer consumers unique benefits, including enhanced autonomy and a stronger sense of consumer identity, it’s clear we are shifting away from this model.

As consumers and businesses navigate and adapt to this new landscape, we are not just witnessing a change in how we consume, but in how we perceive value, community and our roles within it.

This dynamic shift towards an access-based model, fuelled by intrinsic and extrinsic motivations, is driven by the idea of a shared future built on access to goods and services, improved efficiency and collective value.

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Meta’s Threads platform experienced a significant drop in users recently. 

ChatGPT recently experienced a decline in user engagement for the first time since its launch in November 2022. From May to June, engagement dropped 9.7 per cent, with the largest decline — 10.3 per cent — occurring in the United States.

Meanwhile, Meta’s Threads platform experienced a significant drop in user numbers, going from more than 49 million users on July 7 to 23.6 million active users by July 14. In the same time frame, the average time users in the U.S. spent on the app dropped from a peak of 21 minutes in early July to just above six minutes.

In the tech world, companies are always racing to be the first ones to introduce new innovations, aiming for the “first mover’s advantage.” This refers to a firm’s ability to get a head start over competitors by being the first to enter a new product category or market.

However, being a trailblazer doesn’t guarantee an easy ride. While there are perceived benefits, there are also a plethora of challenges that arise.

A news story about what the drop in Meta Threads engagement means for the social media app.

The recent declines of Threads and ChatGPT attest to this reality, demonstrating that rapid and widespread acceptance doesn’t necessarily lead to long-term success.

There are a few reasons why a fast adoption isn’t necessarily the key to success including unsustainable growth, inadequate scaling infrastructure and a lack of user retention strategies.
Unsustainable growth

The idea of unsustainable growth stems from a platform’s inability to uphold or maintain the quality of the user experience while scaling up at a rapid pace.

This is where the real challenge lies: being able to effectively scale up a product or service. It is precisely at this junction that the concept of unsustainable growth intersects with the Gartner Hype Cycle.

The Gartner Hype Cycle is a model that shows the stages of emerging technology adoption: from the initial hype and inflated expectations, through disillusionment and skepticism, to practical and mainstream productivity.

In the context of unsustainable growth, products like ChatGPT and Threads appear to have reached the stage known as “peak of inflated expectations,” where the publicity of a new product generates over-enthusiasm and unrealistic expectations. During this stage, users rapidly adopt the product due to its novelty and the hype surrounding it.

However, this stage often leads to the “trough of disillusionment.” During this stage, the product fails to meet users’ unrealistic expectations, causing a decline in their interest.

It indicates the product’s growth may have outpaced its ability to provide an excellent user experience. Without enhancing the product based on user feedback, declining user engagement will ensue.

This rise and fall underscores the challenge of achieving sustainable growth in the face of rapid adoption. The initial hype often attracts a massive influx of users, but without a clear, scalable strategy for maintaining quality and engagement, platforms can quickly lose their appeal.

Inadequate scaling infrastructure

When a platform’s user base expands at a rapid pace, the question of whether that platform’s infrastructure can scale to the demands of its users becomes critical.

The sudden influx of users that accompanies a successful product launch can be a double-edged sword; it brings a wealth of opportunities for data collection, user feedback and revenue, but also tests the scalability of the platform’s infrastructure.

If the underlying technology, support services or operational strategies are not built to scale, the product might suffer from slow loading times, frequent crashes or a lack of timely customer support — all of which are detrimental to the user experience and a product’s long-term success.

For instance, OpenAI, the company behind ChatGPT, had to limit ChatGPT-4 users to 25 messages every three hours due to infrastructure constraints — even for those with a paid membership. While this helps manage the infrastructure load, it presents a challenge from the user’s perspective.

Users who were accustomed to unlimited interactions with ChatGPT-3 now find themselves paying for a service with limitations. This may inadvertently dampen user engagement and drive some users away, underscoring the delicate balance between managing infrastructure and maintaining user satisfaction.

Lack of user retention strategies

One reason why tech businesses struggle to retain users is because they don’t prioritize user-centered design. By failing to incorporate user feedback in product development, businesses can end up offering a product that doesn’t meet user needs.

In addition, businesses must provide effective support for users. Insufficient or unclear onboarding may leave users feeling lost and overwhelmed, leading them to abandon the product. In the case of ChatGPT, OpenAI provides a basic explanation of platform usage, but users are primarily responsible for exploring it themselves.

Users experiment with prompts without a clear understanding of how to generate impactful responses, resulting in uncertainty and frustration. This lack of guidance may contribute to lower engagement rates, as observed in the recent decline.

Lastly, increasing concerns about security threats and privacy have raised questions about how new technologies are protecting their users. The conflict between the need for more personalized experiences and privacy can give rise to a phenomenon called the personalization-privacy paradox.

As individuals grow increasingly uneasy about how their personal information is stored, the lack of proper regulations can lead to a decline in the use of personalized services or technologies.

While rapid user adoption is a promising start, it doesn’t guarantee long-term success. Striking the right balance between growth and infrastructure scalability, adopting a user-centric approach, maintaining user trust and investing in continuous innovation are the cornerstones for enduring success in the competitive tech landscape.

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To improve the versatility and quality of typical remote-system surveying data, Toronto Metropolitan University (TMU) engineering alumni Robel Efrem (mechanical) and Alexandre Coutu (electrical) teamed up with Sajad Saeedi from TMU’s Department of Mechanical and Industrial Engineering. In partnership with the alumni’s company, Rosor Corp., they develop near-surface, remotely piloted aircraft systems that support multi-datatype output surveying, such as geophysical and topographic, in a single pass.

These long-range survey drones will improve geophysical data collection using custom-designed sensor suites, improved low-altitude accuracy, longer stamina and untethered, long-range communication systems. Enhanced geophysical survey data can provide mining investors greater insights into national and global mining resources, help solve demand shortages through mineral discoveries, and support environmental monitoring and developing technologies like electric vehicles.

Funding for this project by Mitacs. To learn more about how Mitacs supports groundbreaking research and innovation, visit the Mitacs website.

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