getting started with lean ai - artificially intelligent …...approach of lean with the scaling...

A R T I F I C I A L L Y I N T E L L I G E N T C L A I R E . C O M

G E T T I N G S T A R T E D W I T H

L E A N A I

Elevating Your Ideas to Build Something Impactful with Lean AI


There’s No Such Thing As A Bad Idea, But Not All Ideas Are Commercially Viable

Everyone is jumping on the artificial intelligence bandwagon these days.

You will see people creating awesome projects showing off their machine learning skills, but do these projects actually deliver value?

It’s one thing to create a neural network that can accurately classify bats, but what value does it have?

There have been some high profile examples of big budget AI projects that have ultimately failed.

This can be because they focused too much on the tech and not its application in the real world.

One famous example is IBMs healthcare AI that was slammed by Doctors in production for miss-diagnosing patients with potentially fatal results.

Focussing on the Customer can help you avoid these issues. Today we will discuss some techniques to help you do that effectively.

H A V I N G T H E I D E A


An Introduction to Lean AI

There are seven main principles of running a project in a Lean way.

• Always focus on the customer• Understand how work really

happens• Make your processes flow

smoothly• Reduce waste and concentrate on

value• Stop defects through removing

variation• Get buy-in from the team through

collaboration• Make your efforts systematic and

scientificThe most important part of the whole process is to focus on the customer.

By combining the customer-focused approach of lean with the scaling power of AI you’re able to develop something truly impactful.

Instead of getting caught up in the hype you can focus on the customer get to the root cause of the problem and build out a simple solution to solve it.

Once your solution is in place you can create a feedback loop with your customer to develop continuous improvements.

L E T ’ S G E T S T A R T E D !


Reverse Engineering From the Solution

One of the easiest ways (at least on the surface of it) to get started with having ideas with impact is to work backwards from the solution.

One way you can do this is by putting yourself in your customer’s shoes and asking the 5 whys.

In this process, you start with the idea and work through it to understand the true value. If your idea is solid this should be fairly easy.

However, if it is not, you will end up with some more work to do refining it into an idea with impact.



THE 5 WHYS EXERCISE Why does your customer need your project?Y 1

My customer needs to be able to understand whether or not a tumour is malignant or benign with a high accuracy so they can prescribe the right treatment

So you know they need Your Project because of Y1 . But Why does your customer need Y1?Y 2

So you know they need Y1 because of Y2 . But Why does your customer need Y2?Y 3

Because they have a job to look after the patients wellbeing and to give accurate treatment to their patients


It can be challenging to come up with an accurate treatment from complicated data, especially when the data is not always clear cut

Because they need to be able to prescribe the right treatment for the patient

So you know they need Y3 because of Y4. But Why does your customer need Y4?Y 5

Because my customer does not have a lot of time always or may not have seen many examples of the specific patient

situation before. Therefore they need help.


THE 5 WHYS EXERCISE Why does your customer need your project?Y 1

So you know they need Your Project because of Y1 . But Why does your customer need Y1?Y 2



So you know they need Y3 because of Y4. But Why does your customer need Y4?Y 5


Working Backwards From the Solution - Getting StartedThe working backwards process is gaining momentum and often credited as the reason for Jeff Bezos’s success with Amazon.

The idea behind the working backwards process is that you start with the Customer and work backwards to understand exactly what you need to build.

Ask yourself:• Who is the customer?• How do you want them to feel about

your project?• What do they need to feel like that?• How do you know what they need?• How will you give them what they

need?• How will you measure success?

When you are developing projects with AI, or any project, you need to stay connected to your customer need.

Other questions to ask with machine learning projects:• Does this really need machine learning?• What data do I need?• How will I get that data?• What algorithm will give the customer

the result they need in the easiest way for them?



STARTING A PROJECT CHECKLIST

Who is your customer?Who is the person who will ultimately use the product you are developing

Why do they need this product?Complete the 5 why’s so you can clarify the needs

What do I need to get started?Now you know what you need at the end, work backwards to understand how you get there. i.e. what data do you need?

A checklist of items to look at when building out your own data science profile

What is the first step?Time to map out the project and understand what you need to do based on your working backwards

Does this problem really need a machine learning solution?Machine learning is not always the right thing to do for a project - check to make sure you need it otherwise it could be a costly mistake.

How will I measure success?Decide this before you start - if not you may accept a sub-par solution that doesn’t meet the customer need

How will you get feedback from Customers to iterate?Think about how you will build a feedback loop into your project before starting


Notes

getting started with lean ai - artificially intelligent …...approach of lean with the scaling...

Documents