No-Code Machine Learning for People Data: A Culinary Approach

With the introduction of One AI Recipes, One Model has created an intuitive interface for no-code machine learning in people analytics.

One AI Recipes (Recipes) are a question-and-answer approach to framing your people data for predictive models that answer specific people analytics questions. Adding this capability to the existing One AI automated machine learning (autoML) platform results in a more accessible end-to-end no-code solution for delivering AI from right within your people analytics platform. 

We call them Recipes because they walk you through each of the steps necessary to create a delicious dish; a predictive model.  Simply select the ingredients from your data pantry in One Model then follow the steps in the Recipe to be guided through the process of creating a successful model.  Recipes democratize the production and reproduction of AI models with consistency, accuracy, and speed.

Understanding some of the terminology used above and how it relates to One AI will be useful in explaining why Recipes are so useful.

What is a no-code machine learning platform?

“No-code machine learning platform” is somewhat of a vague term.  The definition is pretty straightforward. A no-code machine learning platform is a tool that enables you to apply artificial intelligence without writing any code.  It provides a guided user experience that takes business context as an input and produces predictions and/or causal inferences as output. 

Where it becomes vague is in the range of complexity and flexibility of these platforms.  

On one end of the spectrum, there are simple-to-use AI builders where the user answers a few questions and is presented with predictions.  These tend to only be useful in very standardized use cases.  There is often very little transparency into what the machine learning model is actually doing.  

On the other end are the complex and powerful platforms like Azure ML.  Azure doesn’t require writing code and is also very powerful and flexible, but it is also complex.  Anyone without a working knowledge of data science would be hard-pressed to create trustworthy models on platforms like this.

One AI is aiming at the sweet (no dessert Recipe pun intended) spot on the spectrum.    Being designed specifically for people analytics, it allows us to leverage the question-and-answer approach of Recipes.  Experienced Chefs can still toss the Recipe aside and cook from scratch though.  The One AI kitchen is well stocked with machine learning tools and appliances at its disposal.

What is autoML?

AutoML is a series of processes or “pipeline” that performs data cleaning and preparation, algorithm selection, and parameter optimization for machine learning.  Performing these tasks manually can be labor intensive and time-consuming and requires expertise in data science techniques.  AutoML automates these tasks while still delivering the benefits of machine learning.  

One AI has always provided an autoML pipeline, albeit one where any default setting can be overridden.  Even so, there were two areas where we knew we could improve:

1. The data structure for analytic purposes is not the same as the data structure necessary for machine learning.  Performing machine learning on data in One Model at times required additional data modeling, a task performed by an expert.

2. Framing up the problem and interpreting the results often required an expert to be involved to ensure accuracy and coherent insights.

Recipes address these challenges.  Recipes both re-frame the data in a way that a machine learning model can work with and provide a coherent statement that explains both what the model will be predicting and how it will be doing so.

How can you benefit from One AI with Recipes?

Resource Savings

Recipes lighten the load on the technical resources that are likely in high demand at your organization.  People analytics is a key strategic business function, yet most people analytics teams aren’t lucky enough to employ Data Engineers, Data Scientists, and Machine Learning Engineers.  These teams often fight for the same technical resources as other teams for people who are very talented but can’t possibly possess a deep understanding of all of the different areas of business in the company.

Predicting and planning for outcomes has become a key deliverable of people analytics teams, yet they’re often not well equipped to succeed.  Companies are increasingly looking for software for automation in HR.  Machine learning tools are making great strides in taking business context as an input and producing useful insights as an output.  The full realization of this functionality is no-code machine learning platforms.

Time Savings

With Recipes, time-to-value for machine learning from your people data is substantially reduced.  The difference in time required to manually perform this work versus leveraging a no-code machine learning platform is stark.  It’s weeks to months vs. hours to days.  Even if you have Data Scientists on staff that have the skills necessary to build custom predictive models, they can save time by prototyping in a no-code environment.

Interpretability

Having the clear statements that Recipes provide that explain what it is you’re predicting and how you’re going about it makes the results easier to interpret.  Contrast this with manual machine learning where details can get lost in translation.  This prediction statement is in addition to the exploratory data analysis (EDA), model explanation/performance, and Storyboards that One AI provides.  One Model also employs a team of experts in the ML and AI space that are available to assist if uncertainty is encountered.

Transparency

Since One AI is part of One Model, your model configuration and performance data is available in the same place as the predictive or causal data and your people data (at large).  Also, your models are trained on YOUR data. These are not “black box” models.  At One Model we emphasize making model performance data easily available anywhere predictive data or causal data is included.

Compliance

As a One Model customer, your potentially sensitive employee data resides in the same place as your machine learning. You do not need to export this data and move it around.  On the flip side, the output from your models can be leveraged in your Storyboards in One Model without exporting or moving sensitive data outside of your people analytics solution.  The predictive outputs can even be joined to your employee dimensions to help you identify where risk sits.

Control and Flexibility

Users have the option of configuring data and settings manually in a very granular way.  Just because One AI offers a no-code option for creating machine learning models doesn’t mean you’re tied to it.  Want to use a specific estimator?  You can do that.  Want to modify the default settings for that estimator?  You can also do that.  Recipes just expand the number of One Model user personas able to leverage AI on their data.

In Summary

One AI Recipes provide a question-and-answer approach to building predictive models that answer key questions in the people analytics space.  The resulting democratization of the production of AI models provides benefits including:

• Resource Savings
• Time Savings
• Interpretability
• Transparency
• Compliance
• Control and Flexibility

You can have all of this as part of your people analytics platform by choosing One Model.  

Since you won’t learn about these Recipes by watching Food Network, schedule a demo here: