Keynote: 

When Can We Trust a Decision Made by a Machine: Building Trustable AI and Detecting Misinformation 

 

Synopsis

With the advent of machine and deep learning, explainability and interpretability has become paramount to traceable and justifiable and explainable results:

when someone's house gets foreclosed, some one is sentenced, an insurance claim is denied, a mortgage application is denied. There are  legal, human, organizational, IP and societal implications of leveraging the augmented intelligence of machines in supporting highly complex and previously only open to highly educated, highly skilled experts in medicine, underwriting, law, adjudication, etc.

The need to create and train unbiased or minimally biased datasets for deep learning in the interests of Fairness, Accessibility and Transparency requires best practices that are not known to organizations embarking on machine learning and AI activities.

In this session we will cover the methods and techniques and best practices to detect, manage and mitigate bias in datasets, deep neural network training, application integration. We will also explore the cognitive biases that lead us to curate date to create less than trustworthy blackbox AI systems, and how to avoid them.

We will explore in detail (code level as well as architecture), the project AlternusVera which detects fakeness or deliberate misinformation in a body of text.

 

Audience:

CTOs, IT managers, Data scientists, machine learning engineers, enterprise architects

 

2. Workshop: Natural Language Processing: Foundations and Applied Research

 

In this workshop we will explore the foundations of NLP/NLU and NLG (processing, understanding and generation of natural language)

This will include a case study of Project AlternusVera which we will walk through and provide attendees with code .

AlternusVera ingests a corpus of documents and provides a misinformation index that assesses the reliability of the content against 35 factors.

Dr. Ali Arsanjani is the Director of Cloud Partner Engineering at Google Cloud, and Head of AI Center of Excellence, where he leads the development of strategic co-innovation partnerships in the fields of Generative AI, Data/Analytics & Predictive AI/ML. His team specializes in co-innovation with ISV and GSI partners as they run, integrate and build on GCP across the ML Lifecycle. Ali also works closely with product management to shape the direction of Google's AI and analytics offerings from a cloud perspective.

 

In addition to his role at Google Cloud, Ali is an Adjunct Professor at San Jose State University and the University of California, San Diego, where he teaches and advises students in the Masters in Data program and the Data Science Institute, respectively.