My team-mate is machine.
Are you ready to work with a machine teammate?
So now AI will tell you how to do programming. Now there are various robotic AI leads and co-developers available who would check your code and give suggestions for example code mentor, an architecture mentor, a security mentor, and a performance mentor.
Following teammates are making the waves.
AIAD is also called Mendix Assist, which currently consists of two virtual co-developer bots: MxAssist Logic Bot and MxAssist Performance Bot. The smart apps capabilities include an AWS service connector and the Mendix ML Kit.
MxAssist Logic Bot is an AI-powered virtual co-developer that guides you through modelling and configuring your application logic (microflows). It gives you a real-time and context-driven list of the next best actions based on the application logic already designed and other context-related information.
MxAssist Performance Bot is an intelligent virtual co-developer that assists you in improving the performance of your app by inspecting your app project model against Mendix development best practices while you are building your application in Mendix Studio Pro.
The OutSystems AI Mentor System is a set of AI-based development and quality analysis tools that is intended to support teams throughout the software development lifecycle.
The OutSystems AI Mentor System includes a code mentor, an architecture mentor, a security mentor, a performance mentor, and a maintainability mentor, which provide coding assistance and check for architectural, security, performance, and maintainability issues.
Appian 23.2 includes three AI skills:
Document Classification-automatically classify and route documents.
Document Extraction- extract important text from structured documents so you can use that data in your applications with little effort.
Email Classification-classifies emails based on business-specific labels, making it easy to route email messages to the correct team or aid in case creation.
Jasper, a GPT-3-based content writer, can write blogs, social media and marketing copy, and ads. It’s primarily used by marketers as a writing assistant to help get writing done quickly.
Decision Making
In decision making, we need to consider various factors
1. Is the problem is well known and model is already trained.
2. What is the risk level? Even if risk is low, still humans and machine need to work together. And this new learning will train the machine. What required is human–machine collaboration.
3. How to avoid blame game? Who is accountable for the decision outcomes in human–machine teams?
When a machine is a teammate, a human must own the accountability
and responsibility of the machine’s decisions.
It stands to reason that when an AI teammate has decided, the human teammate needs to be able to explain why a decision was made.
Conclusion
We human are creative and not interested in doing repetitive tasks. Here AI can empower us and our digital team mate with various skills can help us in reducing effort. We just need to be careful, collaborative and caring while working with machine team mate 😁.
References
https://www.youtube.com/watch?v=tdUwWOZPn1M
https://www.infoq.com/articles/sociotechnical-implications-using-machines-teammates/
