Top 5 Gotchas in AI

Make an IIIMPACT - The User Inexperience Podcast

Hey there listeners, Makoto here, and welcome to another insightful episode of Make an IiIMPACT! Today, we're diving deep into the world of AI integration and exploring the five crucial gotchas you need to watch out for.

Joining me are my co-hosts Brynley Evans and Joe Kraft, who bring a wealth of experience and knowledge to the table.

In this episode, we'll be discussing a range of topics that are essential for anyone looking to harness the power of AI in their software.

First, we'll discuss the concept of tokens as a measurement of AI currency and the importance of cost management when using tokens in AI models. We'll also touch on the cost structure of using AI models like Chat GPT and Microsoft Copilot and emphasize the need for budgeting and monitoring token usage to avoid unexpected costs.

Next, we'll delve into the crucial role of data diversity in preventing bias in AI decision-making, and the necessity of monitoring and auditing data sources to ensure transparency. We'll also discuss the significance of inclusive design in avoiding biases and the concerns surrounding ethics, transparency, and bias in AI developments.

We'll then move on to the topic of adversarial attacks and how AI models can be tricked by intentionally designed input data, leading to misinformation and affecting business operations. We'll draw comparisons to jailbreaking and discuss the threats posed by manipulating data sources and introducing malicious data during AI model training.

Furthermore, we'll explore the risks of model inversion attacks, where attackers can reverse engineer and infer sensitive information from the training data of AI models created by other companies. We'll also discuss the importance of privacy and data protection when using AI services, and the potential for bias and discriminatory patterns in AI models if left unchecked.

Lastly, we'll touch on the significance of quality training data, the challenges of caching answers for repeated questions, and the use of hybrid models to balance scripted flows with AI responses. We'll also briefly discuss the role of tokens in managing GPU resources and the security and privacy considerations related to AI model storage and data access.

So, buckle up and get ready for an informative and thought-provoking episode as we navigate the complexities of AI integration and uncover the five gotchas you need to be aware of. Don't forget to like and subscribe to our channel, and let's dive in!

Timestamps:
00:00 Language model tokens represent text currency.
05:34 Budgeting and monitoring AI usage is crucial.
08:43 Token cost tied to processing, infrastructure, prompting.
11:00 Major services don't seem to offer caching.
14:18 AI security concerns and specific gotchas discussed.
19:51 Manipulate data sources to gain business advantage.
22:40 AI model inversion attacks, reversing sensitive data.
24:52 Caution and privacy critical with using AI.
27:08 Neutral hiring process removes human biases. Ads emphasize fairness and efficiency.
33:22 Quora faces backlash for using AI. Ethical challenges.
34:18 Sourcing trustworthy data for AI models is crucial.
39:55 Ethics in AI, need for slower transition.
40:51 AI competition driving companies to invest heavily.
44:40 Ethical dilemma: human vs AI decision-making.
48:00 AI integration requires education for unlocking potential.
52:50 Software maintenance and scalability are crucial.
55:04 Create flexible tooling to pivot and adapt.

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Bios:

Makoto Kern - Founder and UX Principal at IIIMPACT - a UX Product Design and Development Consulting agency. IIIMPACT has been on the Inc 5000 for the past 3 consecutive years and is one of the fastest-growing privately-owned companies. His team has successively launched 100s of digital products over the past +20 years in almost every industry vertical. IIIMPACT help clients get from the 'Boardroom concept to Code' faster by reducing risk and prioritizing the best UX processes through their clients' teams.

Brynley Evans - Lead UX Strategist and Front End Developer - Leading large-scale enterprise software projects for the past +10 years, he possesses a diverse skill set and is driven by a passion for user-centered design; he works on every phase of a project from concept to final deliverable, adding value at each stage. He's recently been part of IIIMPACT's leading AI Integration team, which helps companies navigate, reduce their risk, and integrate AI into their enterprise applications more effectively.

Joe Kraft - Solutions Architect / Full Stack Developer - With over 10 years of experience across numerous domains, his expertise lies in designing, developing, and modernizing software solutions. He has recently focused on his role as our AI team lead on integrating AI technology into client software applications.

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Keywords:
AI ethics, Global AI standards, AI societal impact, AI workforce displacement, AI competition, AI bias, AI legislation, AI decision-making, AI integration challenges, Data quality, Data preparation, Markdown format, AI change management, AI education, AI training, Digital transformation, AI skepticism, AI maintenance, AI scalability, AI tokens, AI cost management, AI models