Exploring Important show stoppers of AI
While AI offers numerous opportunities, it is essential to recognize the constraints that you, as a business, must navigate. Here are two significant challenges to consider:
Product-Policy Fit
Businesses must now account for "product-policy-fit" in addition to product-solution-fit and product-market-fit, due to emerging AI regulations. These evolving laws worldwide will impact the design and deployment of AI functionalities, sometimes even restricting or prohibiting certain applications. The success of innovations increasingly depends on compliance with these new regulations, which means that standards and legislation will play a critical role in bringing products and services to market.
Examples & reflections:
- Europe is a forerunner in AI regulation (EU AI Act). The EU legislation contains a set of measures that put safeguards in place when AI algorithms make decisions and/or automatically execute decisions that could impact someone's life. Providers of AI solutions should include mechanisms to verify the correctness of the decision and avenues to hold individuals accountable if the decision is found to be incorrect. The legislation impacts all products entering the EU market.
- An autonomous vehicle manufacturer must navigate complex safety regulations and standards. Compliance with evolving AI safety laws and restrictions on autonomous driving features can delay product development and market launch.
- A software engineering firm creating AI-driven cybersecurity tools must navigate international data protection laws. These regulations can restrict how AI algorithms process and store data, influencing the design and functionality of the tool.
Gen AI has intellectual property issues
Generative AI is increasingly used in the creative industry, but its legal implications are still unclear, particularly regarding copyrights, ownership of AI-generated works, and the use of unlicensed content for training. Courts are exploring how intellectual property laws apply to generative AI, but much remains uncertain. This creates a complex landscape for businesses to navigate, as the legal framework for AI-generated content is still developing.
Examples & reflections:
- IP considerations can be important criteria to select the GenAI tools that a company uses. Some AI tool providers (e.g., Microsoft Copilot) offer guarantees that the produced output is free of copyrights and that the provided data will not be used for training the algorithm. This comes, of course, with a price, as most free available tools do not provide that guarantee.
- A graphic design company using generative AI to create artwork faces challenges in determining copyright ownership. Uncertainty about whether AI-generated images can be copyrighted or if using AI trained on unlicensed content is legal complicates their operations and legal standing.
- A manufacturing company using AI to design innovative machinery parts faces challenges in patenting AI-generated designs. The legal ambiguity around whether AI-generated inventions can be patented creates obstacles in securing intellectual property rights.
- Software engineers often use generative AI tools to improve the programs they write. This can impose risks, as illustrated by the (in)famous Samsung leak, after sensitive source code was improved with ChatGPT. Through this major leak the source code became available for everyone, because it was used for training the next versions of ChatGPT.
Define the GenAI gamefield in your company
OPPORTUNITIES
Generative AI (GenAI) will revolutionise the way businesses operate, by making advanced AI technologies more accessible and enabling transformative customer experiences and self-learning applications. Let's delve into the specific opportunities GenAI can bring to your company.
CROSSROADS
GenAI presents several ambiguous situations or "crossroads", where the implications of GenAI are not entirely clear yet. These require careful navigation and strategic planning.
