Skip to main content

AI with great power comes responsibility

[PLACEHOLDER]

Generative AI continues to be front and centre of all topics. Companies continue to make an effort for making sense of the technology, investing in their teams, as well as vendors/providers in order to “crack” those use cases that will give them the advantage in this competitive market, and while we are still in this phase of the “AI revolution” where things are still getting sorted.

 

Photo by Google DeepMind on Unsplash

I bet that Uncle Ben’s advise could go beyond Peter Parker, as many of us can make use of that wisdom due to the many things that are currently happening. AI would not be the exception when using this iconic phrase from one of the best comics out there.

Uncle Ben and Peter Parker - Spiderman

A short list of products out there in the space of generated AI:


I mean, if you think, like me, that IntelliSense was/is cool, then products such as Copilot and Tabnine, will blow your mind, as you get your own “AI pair programmer” providing you with:

  • Suggestions as you code
  • Writing functions based on the comments you provided
  • Creates unit test for the code you wrote

Allowing you to accelerate the velocity of your development team. According to GitHub research, Copilot is a big success, improving focus by 74%. It also made users feel 88% more productive and efficient by automating repetitive tasks by a staggering 96%.

AI is also a game changer for how we are levering the current search engine providers, and how those tools are, and will continue to evolve because of it (Bing is a good example on how they made AI accessible as part of their search offering). This is because now users can perform their searches asking complex questions. In addition, users are able to receive personalized results, as well as receiving direct, and immediate, feedback. 


AI and its challenges

While experiencing all the great use cases and advantages that Generative AI is providing at one’s fingertips, we are also discovering new challenges (or existing ones that have immediately become more complex). Just to mention a few:

  1. Copyright issues,
  2. Lack of accuracy within the suggestions provided by the algorithm,
  3. Cheating the system/processes,
  4. Students submitting papers generated by AI systems,
  5. Candidates utilizing AI for resumes and interviews,
  6. PII data risks

The lawsuit cases appear to be just the beginning:

  • OpenAI, creators of ChatGPT, receives a lawsuit alleging it stole people’s data (for more go to the business Insider article here )
  • “Microsoft and its computer code-sharing website GitHub, as well as artificial intelligence firm OpenAI, are being sued in California. A proposed class-action lawsuit claims the firms’ AI-powered programming tool Copilot infringes copyright by using millions of lines of human-written code without proper attribution. It is the first big copyright lawsuit over AI and potential damages could exceed $9 billion.”

Conclusion

While this AI “hype” that we are experiencing can be exciting for some, scary for others, challenging for a few, as technology has accelerated faster than expected; the reality is that “Generative AI” is among us.
It will be an important aspect to adopt/tackle/leverage by companies, as well as by individuals, and therefore it needs to be used with the proper ethics and responsibility.

Trending posts

Demystifying OKR Scoring

You have probably read that one of the many good things about OKRs is that it provides structure and clarity to work towards common goals. It helps connect company, teams and individuals’ objectives to measurable results.   Photo by Garreth Brown via Pexels In a previous Beolle article, Herak wrote about HOSKR and OKRs. In this iteration we will focus on the OKR scoring. Measuring the “How” The KRs in OKRs are the Key Results. With them we measure the progress towards the Objectives we have set. So how do we score them in a way that makes sense, and measure the success? Few “gotchas” before we start Grades are an indication where you're going. In OKRs, scoring between .6 to .7 is your target. Scores between .8 and 1.0 are rare, meaning they are not the usual. If you find yourself completing all your OKRs within this range then something is not correct, for example, your Objectives are not Ambitious enough, meaning you always knew you (or your company or your team) were going to ach

AI bias

Objectivity can be challenging. Machines are not shielded from this by any means. As humans we are leveraging technology in a progressive manner, making our lives easier, becoming an extension of ourselves in our day-to-day existence. By trying to simplify things, complexity creeps in (it is ironic, I know!), and as we try to create something for the good, very often it can be used to go against the principle upon why they were created in the first place.   Photo by Pavel Danilyuk from Pexel Therefore, as creators of this technology, usually with the best intentions, it is understandable when model predictions become susceptible to bias. Those in charge of building the models need to be aware of the common human biases that will find their way into the data used, allowing them to take proactive mitigation steps. To help remove those biases then we need to have structure. A framework that allows us to build AI systems in an ethical manner that can benefit our communities. AI ethics is

What it means to be product led

Many successful organizations including Miro, Figma, Spotify, Atlassian are using products as vehicles to drive customer acquisition and growth. These organizations use their products at the centre of their strategy to win customers and retain them.    Photo by Miguel Á. Padriñán via Pexels If you use any of these tools you are aware of the free trials and freemium versions of these products. These organizations use free versions to generate prospects, drive adoption and convert to paying customers. These organizations are always customer focused and drive to provide friction-less customer experience.  Recently I learned about the inner workings of these organizations by taking the course from Mind your Product and Pendo . Currently the course is available for free and I recommend signing up for the course while the offer is available. Please find the details at the end of the post.  I found the course very insightful and I summarized three (3) key pillars of being a product led organ

This blog uses cookies to improve your browsing experience. Simple analytics might be in place for pageviews purposes. They are harmless and never personally identify you.

Agreed