The InfoQ Podcast
The InfoQ Podcast
InfoQ
Grady Booch on Today’s Artificial Intelligence Reality and What it Means for Developers
32 minutes Posted Feb 22, 2019 at 9:02 am.
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Show notes
Today on The InfoQ Podcast, Wes Reisz speaks with Grady Booch. Grady is well known as the co-creator of UML, an original member of the design patterns movement, and now work he’s doing around Artificial Intelligence. On the podcast today, the two discuss what today’s reality is for AI. Grady answers questions like what does an AI mean to the practice of writing software and around how he seems it impact delivering software. In addition, Grady talks about AI surges (and winters) of over the years, the importance of ethics in software, and host of other related questions.
Why listen to this podcast:
- There have been prior ages of AI that has lead to immediate winters of where reality set in. It stands to reason, there will be a version of an AI winter that follows today’s excitement around deep learning.
- AIs are beginning to look at the code for testing edge cases in software and do things such as looking over your shoulder and identifying patterns in the code that you write.
- AIs will remove tedium for software developers; however, software developer is (and will remain) a labor-intensive activity for decades to come.nAI is another bag of tools in a larger systems activity.
- Much of the AI developers are young white men from the United States. That has a number of inherent biases in this fact. There are several organizations that are focused on combating some of these biases and bringing ethical learning into the field. This is important for us to be aware of and encourage.
- The traditional techniques of systems engineering we know for building non-AI systems will still apply. AI’s are pieces of larger systems. That might be really interesting parts, but it’s just a part of a larger system that requires a lot of non-AI engineering use cases.
- Early machine learning systems were mostly learn and forget systems. You teach them, you deploy them, and you walk away. Today, we do continuous learning and we need to integrate these new models into the delivery pipeline.
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