AI Digital Transformation with Dr. Jerry Smith

02/11/22 • 29 min

Dr. Jerry Smith welcomes you to another episode of AI Live and Unbiased to explore the breadth and depth of Artificial Intelligence and to encourage you to change the world, not just observe it!

In today’s episode, Dr. Jerry is going to talk about AI digital transformation, a process that has evolved into some capabilities that are believed to be transformational. Dr. Jerry is going through the story circle, outlining the reasons why digital transformation is important and its several components.

Key Takeaways:

Challenges in traditional digital transformation:
- Transforming the company digitally (which is not the same as digitally transforming you).
- Digital transformation is a continuous adapting process.
First problems that all organizations have:
- Organizations collect information and store it without seeing the immediate value in storing data.
- What can data tell me? Does any of this data tell me about the behavior of the customer?
The cognitive phase is about the human cognition applied to data; Dr. Jerry explains how it is done through our five senses:
- Vision.
- Voice (we can tell how someone is feeling by their different tones).
- Language processing.
- Sentiment analysis.
- Cognitive search on decision-making.
Causality: All data is interesting, but it is not all important.
- Certain kinds of data are causal to certain kinds of problems.
- Find what is causal to your business concern.
Levers of change:
- If you can find a way to change a variable to go from A to B then you are going to change the output.
- We move from a passive understanding of the world (collecting data) to a deep insight phase where we can now change the variables and learn deeply.
A digital surrogate is a predictor with causal inputs, it is a digital representation of the entity that is important to us.
- We can predict how the world is going to change.
The Optimization Stage:
- Evolutionary computing is an optimization technique that allows us to seek in the complete search base in a very time-friendly way, and find the optimal result.
- We apply evolutionary computing to figure out how to best treat inputs to achieve an optimal outcome.
The Implementation stage:
- We take these inputs and transition them into real-life programs in the real world.
- If you apply this program, you will create change, it is unavoidable.

Stay Connected with AI Live and Unbiased:

Visit our website AgileThought.com

Email your thoughts or suggestions to [email protected] or Tweet @AgileThought using #AgileThoughtPodcast!

Learn more about Dr. Jerry Smith

Dr. Jerry Smith welcomes you to another episode of AI Live and Unbiased to explore the breadth and depth of Artificial Intelligence and to encourage you to change the world, not just observe it!

Key Takeaways:

Challenges in traditional digital transformation:
- Transforming the company digitally (which is not the same as digitally transforming you).
- Digital transformation is a continuous adapting process.
First problems that all organizations have:
- Organizations collect information and store it without seeing the immediate value in storing data.
- What can data tell me? Does any of this data tell me about the behavior of the customer?
The cognitive phase is about the human cognition applied to data; Dr. Jerry explains how it is done through our five senses:
- Vision.
- Voice (we can tell how someone is feeling by their different tones).
- Language processing.
- Sentiment analysis.
- Cognitive search on decision-making.
Causality: All data is interesting, but it is not all important.
- Certain kinds of data are causal to certain kinds of problems.
- Find what is causal to your business concern.
Levers of change:
- If you can find a way to change a variable to go from A to B then you are going to change the output.
- We move from a passive understanding of the world (collecting data) to a deep insight phase where we can now change the variables and learn deeply.
A digital surrogate is a predictor with causal inputs, it is a digital representation of the entity that is important to us.
- We can predict how the world is going to change.
The Optimization Stage:
- Evolutionary computing is an optimization technique that allows us to seek in the complete search base in a very time-friendly way, and find the optimal result.
- We apply evolutionary computing to figure out how to best treat inputs to achieve an optimal outcome.
The Implementation stage:
- We take these inputs and transition them into real-life programs in the real world.
- If you apply this program, you will create change, it is unavoidable.

Stay Connected with AI Live and Unbiased:

Visit our website AgileThought.com

Email your thoughts or suggestions to [email protected] or Tweet @AgileThought using #AgileThoughtPodcast!

Learn more about Dr. Jerry Smith

Previous Episode

AI Improving Health Care with Tammy Siragusano

Dr. Jerry Smith welcomes you to the inaugural episode of AI Live and Unbiased to explore the breadth and depth of Artificial Intelligence and to encourage you to change the world, not just observe it!

Dr. Jerry is joined today by Tammy Siragusano who is a veteran in U.S. healthcare reform whose focus has been on the enterprise approach to some of the most complex health care problems facing the industry today. She is experienced in healthcare IT, managed care operations, is a PBM-PBM migration specialist, and takes care of a lot of operational issues. Tammy has also led the digital transformation for clinical logistics for drug and utilization review.

In today’s episode, she shares her vast knowledge and experience in the field of AI and shares great ideas and suggestions for better AI implementation in the healthcare field.

Key Takeaways:

Tammy shares why she got involved in the healthcare field

Tammy belonged to the debate team and healthcare was at the center of their attention, a reform was desperately needed due to many delays in the care.
Tammy didn’t join the healthcare field as a software engineer but as a sports medicine practitioner.

Three of the biggest aspects that drive decisions in healthcare:

Watch the pennies, the dollars will take care of themselves.
What is the most convenient way that the patient can receive the care he/she needs?
Where should the focus be to make the biggest long-term impact?

Why is AI needed in healthcare?

Technology has to find a way to disrupt the status quo.
Health practitioners need to focus on patient care.
One-third of healthcare practitioners are already using AI and almost one-half of the other companies are currently exploring it.

What kind of problems is healthcare trying to solve through AI?

Upcoding and regulatory sides are two of the major fields where AI is needed.
AI can make payments easier.

There are three obstacles to AI implementation in the healthcare industry:

limited resources,
different data that is unconnected,
and lack of tools and platforms to develop solutions.

CMS (Centers for Medicare and Medicaid Services) set aside a considerable amount of money for technology companies to use for innovations.

Budget is not an issue; the government will fund projects that develop platforms to create solutions.

What are the biggest problems to focus attention on?

There are performance improvement plans for clinical groups that will be based on outcomes; not only they will have to be doing better but be able to prove it since the reimbursements will depend on it.
Call centers collect very important patient information that could be utilized more effectively with the help of AI.
AI could identify how the patient feels when calling and identify the level of urgency of the call.

What does the future of wearable medical devices look like?

Wearable medical devices will get better and better.
Wearables will help those who are currently restricted in their abilities because of a disease or characteristic of their body.

Tammy talks about the possible uses of AI for prescription monitoring.

There are outreach programs to follow up on how patients are taking their prescription medicine, for them to stay on track with their medication, and find out the reasons why some people are not.

Where do we go from here?

The government is looking to fund great ideas, they are looking for creativity and new technology from the AI world.

Stay Connected with AI Live and Unbiased:

Visit our website AgileThought.com

Email your thoughts or suggestions to [email protected] or Tweet @AgileThought using #AgileThoughtPodcast!

Learn more about Dr. Jerry Smith

Mentioned in this episode:

CMS

Next Episode

Cognitive Services with Dr. Jerry Smith

Dr. Jerry Smith welcomes you to another episode of AI Live and Unbiased to explore the breadth and depth of Artificial Intelligence and to encourage you to change the world, not just observe it!

Dr. Jerry is talking today about Cognitive Services, which is the second part of the evolutionary optimized digital surrogate-based predictions causal AI-driven digital transformation life cycle. Listen to this episode to find what Cognitive Services are, why they are important to businesses, how to identify four key cognitive attributes to your services, and three of the most important services you should start using today.

Key Takeaways:

Before starting with today’s cognitive services, Dr. Jerry goes back a few years to lead us to where we are now.
- In 2016, cognitive services started, but a lot of them were just promises that did not bring economic value.
- Cognitive services missed the connection with the business side, but causality changed that.
What are Cognitive Services?
- Cognitive relates to conscious and mental activities.
- If you are using AI to help you make decisions that relate to your customers, you need to have someone that relates to Cognitive Psychology and understands the psychology of people and the sociology of groups.
- Examples of cognitive services are Speech and Image recognition, Text to Speech, Speech to Text, and searching through vast amounts of information.
What is Cognitive Computing and what are some of its benefits?
- Cognitive computing is the use of computerized cognitive models to simulate human thought processes.
- One benefit of cognitive computing is that it performs well in complex situations where answers and data are ambiguous and uncertain.
What constitutes cognitive computer systems? Four primary characteristics:
- Cognitive computer systems have to be highly adaptive, they have to be flexible enough to learn as information changes.
- Cognitive computer systems have to be interactive.
- Iterative and stateful. Cognitive computer technology can identify problems by asking questions if the state of the problem is vague or incomplete.
- Cognitive computer systems have to be contextual since understanding the context is probably the most critical process in the causal AI digital transformation cycle.
- Cognitive computing is not AI; it uses AI and AI uses cognitive computing.
- Cognitive computing is used when you are dealing with human characteristics in industries like health care and services. Cognitive computing is more about being human than being a machine.
What is data science?
- Data science is the process of studying data, you always get value out of it.
- Machine learning learns the characteristics of the data in different variables in order to make predictions.
- AI is all about making decisions based on the machine learning models and the predictions of tomorrow and asking what are we going to be doing tomorrow as a consequence of that.
What are some of the top cognitive services today?
- Computer vision: consists of pulling out actual information from images.
- Emotion: Analyzing faces and bodies to detect emotional ranges of mood.
- Face: Identify similar faces.
- Content moderation is automatically moderating text, images, or videos, and has profound importance to our society.
Why are cognitive services important?
- Cognitive services allow us to drive behavioral insights from data.
- Data has no intrinsic value; the value of data comes in how we process it, how we look at it, and what questions we ask (which are very subjective and will give different outcomes).
- Behavior, behavior, behavior.