Advertisement

How To Obtain Explainability In AI Systems?

Anukriti

At The Rising 2020, we had a session on yet another widely discussed topic in artificial intelligence — Explainable AI — that has the potential to bring trust among users of ML-based solutions. Anukriti Gupta, Manager – Data Science at United Health Group, discussed why there is a need for identifying the factors that lead to the outcome of AI models.

Anukriti started the session by explaining how AI has proliferated and is assisting businesses in making informed decisions to obtain business growth. Besides, she mentioned that AI drones are being developed to be leveraged in battlefields. However, Anukriti said that even the smallest percentage of error by AI-models could be catastrophic not just on the battlefield but for organisations that are heavily relying on cutting-edge technologies like AI. Consequently, Anukriti stressed on the fact that explainability is the need of the hour to ensure organisations deliver solutions that are effective as well as reliable. 

To further substantiate her argument, Anukriti showed the attendees how AI had failed us in the past. For instance, Microsoft’s AI-bot — Tay — on Twitter went rouge by being biased in 2016. In addition, COMPAS, another AI system, was used by the U.S court under trail for determining potential recidivism risk. It was found that the AI in COMPAS was biased towards the colour of criminals.

THE BELAMY

Sign up for your weekly dose of what's up in emerging technology.

Such instances, along with various privacy concerns, have led to the introduction of regulations such as GDPR, where organisations have to be transparent about their AI-based solutions. Therefore, companies need to actively embrace explainability to avoid any potential penalties for failing to comply with the regulations.

How Can We Obtain Explainability

“As the sophistication increased with advanced algorithms, the accuracy increased, but the explainability decreased,” said Anukriti. For one, we can explain how regression techniques work, but when it comes to deep learning techniques, we call it a black box as it’s difficult to explain. 


Download our Mobile App



However, there are various frameworks such as LIME (Local Interpretable Model-Agnostic Explanations), SHAP (SHapley Additve exPlanations), and ELI5 (Explain Like I’m 5) in the market that can help companies bring transparency in their models. Anukriti utilised employee attrition data and demonstrated the implementation of LIME and SHAP.

Being a model agnostic, LIME works with almost every algorithm. It is not only flexible but also easy to implement. However, some of the advantages of SHAP are its appealing visualisations, which simplifies the process of communicating the factors that were responsible for the outcome that AI models provide. Unlike LIME, that is mostly limited to local interpretability, SHAP offers global interoperability, thereby presenting the contribution of every variable in an outcome. 

Anukriti said everyone should at least work with anyone with an explainability framework and gradually enhance their knowledge to bring trust among stakeholders. For this, she also recommended a book for people who want to get started with explainability.

Eventually, she concluded by saying that explainability is the key for businesses to succeed in the coming years. Therefore, one should obtain knowledge around the explainability of AI models and also stay up to date with its latest developments.

More Great AIM Stories

Rohit Yadav
Rohit is a technology journalist and technophile who likes to communicate the latest trends around cutting-edge technologies in a way that is straightforward to assimilate. In a nutshell, he is deciphering technology. Email: rohit.yadav@analyticsindiamag.com

AIM Upcoming Events

Conference, in-person (Bangalore)
Rising 2023 | Women in Tech Conference
16-17th Mar, 2023

Early Bird Passes expire on 10th Feb

Conference, in-person (Bangalore)
Data Engineering Summit (DES) 2023
27-28th Apr, 2023

3 Ways to Join our Community

Telegram group

Discover special offers, top stories, upcoming events, and more.

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Subscribe to our Daily newsletter

Get our daily awesome stories & videos in your inbox
AIM TOP STORIES

Top BI tools for Mainframes

Without BI, organisations will not be able to dominate with data-driven decision-making but focus on experiences, intuition, and gut feelings.