Process Improvement is the Efficacious Key to Unlocking Artificial Intelligence
Kenny Woods
Results Orientated Operations Professional specializing in Optimizing processes, problem solving, and driving results.
Introduction
Artificial Intelligence is technology that is rapidly evolving, and such, people are constantly discussing its impact and implications. The three conversations that people are having about AI are its ethical implications, potential impacts on jobs, and its role in shaping society and the economy. I like you believe there are some very thought-provoking discussions on these specific topics, however if you grew up with the Jetsons and Artari and got to witness the evolution of the Nintendo glove or turbo button, Let's do this!
Oh and as travel fastpitch coach and dad (14U&16U) I would love my Kids (players) to get virtual BP against the random player that can throw 60 consistently with movement before our tournaments. Or like anyone we can check the GameChanger stats or take notes and input it into a system that can generate the actual like pitcher we are about to face in virtual BP session. (BP - batting practice) (Coach Lisle - Coach Brian Cain - Forgive me)
It Starts with the Process, Effective or Non-Effective?
Without standards, there can be no improvement - Taiichi Ohno
Effective process improvement is key to creating efficient and reliable AI systems. AI systems rely on data, algorithms, and models to produce outputs that can impact businesses' bottom lines. Without proper processes, these outputs can be inaccurate, unreliable, and can cause significant business risks. Incorporating effective process improvement practices ensures that the AI system is aligned with the organization's goals, standards, and inputs. It also provides a framework for continuous improvement, which is essential for maintaining the accuracy and reliability of AI systems.
There is the argument of automation by utilizing what data is accessible, however the data is still coming from an input, which is supported by processes. If you are experienced in using data driven decision making or algorithmic decision making, you too then would be thinking as I am. All of this mentioned comes down to what's the process? "There is Power in the Process." ;)
Where there is no Stanard there can be no Kaizen - Taiichi Ohno
Neglecting Effective Process Improvement:
There is in my professional and humble PI opinion that neglecting effective process improvement in AI can have significant consequences. One of the most significant risks is the production of biased outputs. Bias can occur when an AI system is trained on data that is not representative of the population it is intended to serve. This is the same for systems being trained on process data that is not aligned with compliance or measured outcomes. This can lead to discrimination, unfair treatment, and, in some cases, legal and reputational risks.
Another risk is the production of erroneous or capricious outputs. AI systems are only as good as the data they are trained on, and without effective processes, there is a risk of the system providing outputs that are not accurate or reliable. This can lead to incorrect decisions, which can impact an organization's operations and bottom line.
It's not just a risk, but unsafe and dangerous depending on the industry and how they are using it. Healthcare inaccurate diagnosis, delayed treatment, and even death. Within the Utility field, electric operations clearing lines or opening the wrong switch. Last example or assumption would be military making strategic plans based on the improperly trained model. There is a lot to unpack, however you get the point.
To be fair, most companies using Ai do have this in mind, well based on the ones that are being transparent in their efforts. Most industry experts leading the charge for their industry or company, probably has an expert onboard to guide the journey or at least show them the, "PROCESS."
How Effective Process Improvement Supports AI
Effective process improvement supports AI by ensuring that the AI system is aligned with the organization's goals, standards, and inputs. It also provides a framework for continuous improvement, which is essential for maintaining the accuracy and reliability of AI systems. Effective process improvement helps organizations to identify potential biases, evaluate data quality, and develop strategies to address these issues. It also enables organizations to monitor and evaluate the performance of AI systems, identify areas for improvement, and implement changes to ensure that the outputs remain accurate and reliable.
There is a science to learning and developing the right approach, which should be part of the continuous improvement model for organizations and how process improvement initiatives are deployed and implemented. Note: Be sure to measure your journey, progress, and outcomes. It would be hard to know how far you have come without knowing where you started.
Incorporating Effective Process Improvement into AI Development:
The following steps can be used to develop an effective process improvement framework for AI:
Define the goals and objectives of the AI system: Identifying the purpose of the AI system is diagnostic to advancing an operational process improvement framework. It is critical to identify the envisioned use of the AI system, the target audience, and the anticipated outputs.
Foster a data governance framework: A data governance framework is vital to safeguarding that the data used to train the AI system is accurate, reliable, and representative. It encompasses processes for data quality, data security, and data privacy.
Assess the quality of the data: Assessing the quality of the data used to train the AI system is cardinal to identifying prospective biases and developing strategies to address them.
Develop and test the AI model: Developing and testing the AI model needs a structured approach to ensure that the model is accurate, reliable, and produces the desired outputs.
Monitor and evaluate the performance of the AI system: Monitoring and evaluating the performance of the AI system is critical to identifying areas for improvement and implementing changes to ensure that the outputs remain accurate and reliable.
The above steps are more of an ideal approach in my mind and I'm sure we can unpack that even more as a collaborative discussion. I get it. You might have the better or more informed answer, for now just keep reading and hear me out. Write an article too or blog on the same topic.
Effective Process Improvement in AI:
Effective process improvement has been harnessed in various AI systems. For instance, in the financial sector, process improvement has been used to develop AI systems that detect fraudulent transactions, identify investment opportunities, and predict market trends accurately. In the healthcare industry, process improvement has been used to develop AI systems that can predict diseases, identify risk factors, and improve patient outcomes. Process improvement has also been applied in the retail industry to develop AI systems that can analyze customer data, personalize marketing campaigns, and optimize inventory management.
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Conclusion:
As a process improvement coach with over a decade and a half in continuous improvement, organizational development, data analytics, change management, and operational excellence, I tend to read the tea leaves or between the lines better than most. I see things in processes that others will not see because most want the outcome and don't see the value stream and its processes supporting it. Most just want the outcome without understand the processes.
This is one of many ways to unpack and drive process improvement conversations, however if you want to have an offline conversation, message me! I can be a soundboard, idea generator, planner, executor, implementer. I can do the advising without criticizing, and the consulting without insulting. I know other people you can reach out to if my background and experience does not align with what you are thinking, however let's start with why, or what success looks like based on your specific topic in process improvement.
Artificial intelligence is not a replacement for human intelligence, but a tool that can enhance and augment it. - Ginni Rometty, Former CEO of IBM
Education is only information, if there is no application, so keep learning continuously. - Coach Kenny
Books I own and recommend: To name a few.
Managing to Learn: Using the A3 Management Process to Solve Problems