The Potential of Generative AI
Generative AI has revolutionised the way we interact with technology. By generating human-like text, images, and videos, Generative AI has opened up new possibilities for product development. With the ability to generate content, respond to user queries, and even create new products, Generative AI has the potential to transform the way we experience products and services.
Things to Consider
Understand Your User
Generative AI is powerful, but understanding the needs of your users deeply and how they will interact with your GenAI solution to fulfil those needs remains foundational as with any other product.Being clear about the value your product brings to users, informs the design of your AI features, ensures they are truly user-centric and provides direction to your Data Science teams.
Data is King
Needless to say, access to high-quality data that matches the unique needs of your users and can be used to train your models is crucial to the success of your Generative AI model. Consider data privacy, security, and ethical implications throughout the process.
Ethical Considerations
As with other AI solutions, Generative AI models will also perpetuate biases and stereotypes if not designed with ethical considerations in mind. Ensure that your model is fair, transparent, and unbiased. User safety is a key tenet for your project and all key stakeholders need to be aligned with it.
Transparency and Explainability
Users need to trust the AI they interact with. Design your product to provide transparency and the reasoning behind its outputs. This requires User Experience (UX) design that is built specifically with the AI interaction in mind. For instance, building features that maintain user control and provide feedback, e.g.,
- Allow users to correct or adjust AI-driven decisions, promoting a sense of control and agency.
- Provide feedback mechanisms for users to rate or comment on AI-generated content.
- Offer customisation options to tailor the AI system to individual user preferences.
This importantly builds trust and helps users understand the limitations of the technology.
Challenges and Ways to Overcome Them
Risk Of Unverified Content
Generative AI models are “confidently correct” and can easily mislead users. These models excel at creating unique and interesting content, but this generative nature can often lead to factually incorrect predictions. Being deeply critical and maintaining good human judgement for quality control is therefore key to protect your users. Establish ethical frameworks and guidelines, promoting awareness about the potential risks and consequences to users that will help everyone exercise caution and responsibility.
Maintaining User Trust
Transparency and clear communication are crucial for building and maintaining user trust. Be upfront about the capabilities and limitations of your Gen AI solution, and provide mechanisms for users to provide feedback and report issues.
Buy Versus Build Dilemma
A major tradeoff decision when building Gen AI is products is deciding whether to buy or build the solution. While buying a solution offers faster time-to-market, reduced development costs, and access to expertise. it may lack customization, increased dependency on the vendor, and lack control over the project. Building a solution provides customization to specific business needs, control over the development roadmap, and a competitive advantage, but comes with higher development costs, longer development time, and requires in-house AI expertise.
The best approach depends on your specific circumstances and priorities, factoring in the urgency , customisation needs , budget and technical experience available for the project.
Conclusion
As Product Managers, keeping our users at the heart of everything, thinking hard about ethics, and keeping up with this fast evolving technology remains key. If we get it right, we can truly transform how we build products with Generative AI and really shape future experiences.
