Political Factors

On the policy side, Canada has entered a host of legislation impacting the accessibility and content of information. For instance, the Online News Act was implemented to hold big tech companies accountable for using Canadian news content.

Meta (Instagram and Facebook) and Google must now pay Canadian news sites to use their content. However, Meta has opted out of this agreement and has made news sites unavailable for Canadians on its platforms. This could result in less news being available on some platforms. It could also mean fewer people seeing news from providers. Additionally, news sites may receive less money if they agree to the terms. Google has agreed to pay about C$100m to compensate news organizations who apply by April 30th, 2024.

Another example of recent measures made by the Parliament to regulate online content includes the Online Harms Act, which takes measures to hold individuals and platforms accountable for sharing harmful content. While some of the definitions of “harmful content” and the consequent repercussions are clearly stated in the act, others are vague and could result in a grey area when dealing with enforcement. Similar clauses and vague definitions can be found in the Privacy Act, which regulates how the government of Canada acquires and disperses individuals’ personal information.

These policies aim to protect citizens, communities, and Canadian businesses. However, some clauses may impact daily operations and business practices, like gathering information and reaching a specific audience. CEOs and business leaders, especially in broadcasting, should prioritize the potential impact of these laws when planning strategies.

Economic Factors

Companies developing AI models have seen a huge surge in public investment and interest. Other start-ups are trying to catch the wave of AI and the profits that come with it. The question moving forward is if AI is going to live up to the hype and have such an impact as the trend suggests.

Some experts are saying we are currently in an AI bubble, which means a huge downside risk if this bubble pops. There will likely be some correction in the market, but the lasting impacts of AI are surely here to stay.

Some artificial intelligence tools allow for a great increase in productivity, particularly in office-related jobs. However, as it stretches and combines with robotics, we could see many physical processes automated, replacing jobs, allowing for more creativity, and potentially reducing salary expenses. Robotics could also see an increase in production and market share in the foreseeable future.

As a business leader, it’s smart to carefully choose the companies you buy AI programs from by doing research. Understanding where the company sourced its information to train its AI program and the regulations it imposes on its AI can help evaluate which one to choose.

Some information may be kept secret, but pressure from society is pushing companies to be more open. Doing thorough research can give good results. This process can help you determine if the company has bias or control in its programs. It can also assist you in deciding where to get your AI needs based on technological factors.

Social Factors

Microsoft, Google, and OpenAI, have seen many instances of having to publicly apologize for the results generated by their AI programs, due to biases of information entering into their databases.

Socially, there is growing polarization on the political and ideological fronts, meaning the tolerance for public mistakes from inaccurate, misinformed, or skewed information can cause very real impacts on businesses in brand reputation, customer demand, and talent attraction.

Technical Factors

More tangibly, one significant threat to pay attention to is skewed, inaccurate, or unvalidated data and research. With AI becoming an essential tool in sourcing, analyzing, and driving insight to inform business or competitive decisions, there is a risk of misinformation in the data AI programs are providing.

The “garbage in, garbage out” principle is the best description of why this is happening. AI models are only as good as the data and information they are trained on. If there is bias, inaccuracy, or deceptions in the data they are fed, the answers they generate will be subject to the same imprecision.

Environmental Factors

Although there are no direct impacts on the environment created by AI and new government policy, there is no promise that there won’t be in the future. AI can have the potential to seep into every part of our lives. It is a new information transmission that could sway opinions, science, and behaviours, resulting in a change in the way we interact with our environment.

A possible positive outcome could be an enhanced perspective on environmental issues such as climate change and disease control. With the ability AI has to process and analyze large amounts of data in a short timeframe, we could come to reasonable and actionable solutions more efficiently to mitigate the damage of various environmental issues.

On the contrary, if AI becomes increasingly biased due to lack of or overbearing regulation, it could only exacerbate the polarization of opinion surrounding environmental issues and slow the process of finding clear solutions.

Business leaders should use AI responsibly and consciously, not taking its word for ultimate truth, and contribute to an equitable and understanding discourse that values all perspectives when it comes to environmental and societal issues.

Legal Factors

Tied in with political factors, acknowledging the new policies (mentioned above) that are being implemented considering AI and understanding what they mean for your business’s ability to source information, and the consequences for non-compliance in the handling of information, is important in lowering risk, bias, and avoiding penalties.

Legal challenges arise when AI is used in regular business practices such as hiring, lending, or decision-making. For example, Amazon had to step back from using AI in hiring decisions when they discovered their system had a particular bias against female candidates.

The data that AI is trained on often involves sensitive personal information, and workplace policies should address the use of personal or sensitive information as inputs into AI software, as it is unclear as to how this information will train the AI and be used in future outputs available for the public.

One notable concern surrounding AI is the question of intellectual property (IP). AI is capable of creative human-like artwork or content, in such a case, the owner of the copyright of said work is vague and needs to be refined under copyright law. Updates to laws concerning IP will take time; meanwhile, businesses can draft contracts and internal policies of their own to clarify ownership of content that is created using AI.

Conclusion

This is a unique and valuable dialogue for business leaders in Canada as we see developments in both technology and the policies surrounding their use. This topic requires a lot of nuance and finesse in handling as it can be a politically or ideologically charged topic. Having a conversation with your team about how to best position your messaging, culture, and technological protocols in a way that is suitable for your brand and business would be a valuable process for all leaders. Keeping on top of the trends and developments in the space is the best way to reduce the risk of information inaccuracy or access challenges.

Dive deeper into what business leaders should know about AI by downloading our whitepaper HERE.