The Software Engineering for Machine Learning Applications (SEMLA)
international symposium aims at bringing together leading researchers
and practitioners in software engineering and machine learning to
reflect on and discuss the challenges and implications of engineering
complex data-intensive software systems.
Given the current pandemic situation, SEMLA 2021 will be in the form of
a series of free Webinars.
Speakers include Ben Shneiderman, Nisha Talagala, Q. Vera Liao, Danilo
Sato, Arif Wider, Yingnong Dang, Grace Lewis.
(https://semla.polymtl.ca/2021speakers/)
We invite everyone to join. Registration to the Webinars is free but
required. For the full program and the registration links, please visit:
https://semla.polymtl.ca
To register to all SEMLA 2021 Webinars at once, please visit:
https://www.eventbrite.ca/e/semla-2021-full-registration-tickets-154740638415
SEMLA 2021 Program
==================
Tuesday, June 8, 2021
Speaker: Ben Shneiderman, Professor of Computer Science, University of
Maryland
Title: Human-Centered AI: What it is and how software engineering can
contribute to its success.
Date/time: June 8, 2021, 12:00pm-1:00pm EDT
Registration link:
https://www.eventbrite.ca/e/semla-2021-tickets-154239627879
Abstract:
A new synthesis is emerging that integrates AI technologies with HCI
approaches to produce Human-Centered AI (HCAI). Advocates of this new
synthesis seek to amplify, augment, and enhance human abilities, so as
to empower people, build their self-efficacy, support creativity,
recognize responsibility, and promote social connections. These
passionate advocates of HCAI are devoted to furthering human values,
rights, justice, and dignity, by building reliable, safe, and
trustworthy systems. The talk offers three ideas:
• HCAI framework, which shows how it is possible to have both high
levels of human control AND high levels of automation.
• Design metaphors emphasizing powerful supertools, active
appliances, tele-operated devices, and information abundant displays.
• Governance structures to guide software engineering teams, safety
culture lessons for managers, independent oversight to build trust, and
government regulation to accelerate innovation.
The talk will emphasize the software engineering practices that will
make machine learning more reliable, by increasing audit trails,
reducing bias, and supporting explainability. These ideas are drawn from
Ben Shneiderman’s forthcoming book (Oxford University Press, January
2022). Further information at: https://hcil.umd.edu/human-centered-ai
Join the Human-Centered AI Google Group at:
https://groups.google.com/g/human-centered-ai and follow
@HumanCenteredAI on Twitter.
----------------------------------------------------------
Tuesday, June 15, 2021
Speaker: Nisha Talagala, CTO/VP of Engineering at ParallelM
Title: AI Literacy: Its Role in the Workforce of the Future
Date/time: June 15, 2021, 12:00pm-1:00pm EDT
Registration link:
https://www.eventbrite.ca/e/semla-2021-tickets-154319145719
Abstract:
The AI market is projected to grow to $190 Billion by 2025. AI is being
used in every industry and is projected to be a core skill for the
future. While lack of production machine learning (MLOps) was a limiter
in the last few years, these limits are starting to be overcome, with
MLOps practices now standard in many organizations. More businesses are
starting to see positive returns from their AI initiatives. We are
shifting to a new phase of AI development, where broad segments of the
non-technical workforce are encountering AI in their job roles. This is
both exciting and fraught with peril. Instances of AI failures, legal
issues, and ethical issues are rising. There is pressure on AI
development to accommodate not just data scientists but people from all
walks of life. To achieve the next levels of returns from AI require
technologies and solutions that combine AI and human intelligence.
In this talk, we discuss recent AI and Machine Learning technology
trends and the role of MLOps in driving AI commercial success. We then
discuss what it takes to bring AI knowledge out of the technical domain
and into the broader workforce, and technology trends like low-code that
enable broad adoption. We will then discuss a framework for AI Literacy
– the Four Cs – and experiences of bringing AI literacy to individuals
worldwide.
----------------------------------------------------------
Thursday, June 17, 2021
Speaker: Q. Vera Liao, Research AI at IBM T.J Watson Research Center
Title: Questioning the AI: Towards Human-Centered Explainable AI (XAI)
Date/time: June 17, 2021, 12:00pm-1:00pm EDT
Registration link:
https://www.eventbrite.ca/e/semla-2021-tickets-154319603087
Abstract:
Artificial Intelligence technologies are increasingly used to make
decisions and perform autonomous tasks in critical domains such as
healthcare, finance, and criminal justice. The needs to understand AI in
order to improve, contest, develop appropriate trust and better interact
with AI systems have spurred great academic and public interest in
Explainable AI (XAI). Recently, open-source toolkits, including IBM
Research’s AI Explainability 360, are making a growing collection of XAI
techniques into practitioners’ toolbox. My colleagues and I at IBM
Research conduct human-computer interaction (HCI) research that aims to
empower AI practitioners to make effective and responsible use of such a
toolbox to create good XAI user experiences. Meanwhile, our work
provides insights into real-world user needs for AI explainability to
inform gaps and opportunities for XAI algorithmic research. Our work
follows two complementary paths. First, we conduct HCI research by
designing and studying XAI systems of various use cases in the AI
lifecycle. Second, we study AI design practices of product teams and
engage with the design community to develop and advocate for
user-centered design processes for XAI. I will conclude the talk with
lessons learned for bridging the process of creating responsible AI
systems and empowering people in the process.
----------------------------------------------------------
Tuesday, June 22, 2021
Speaker: Danilo Sato and Arif Wider, Head of Data & AI Services at
ThoughtWorks UK and professor at HTW Berlin
Title: Continuous Delivery for Machine Learning
Date/time: June 22, 2021, 12:00pm-1:00pm EDT
Registration link:
https://www.eventbrite.ca/e/semla-2021-tickets-154319976203
Abstract:
Machine Learning applications are becoming popular in our industry,
however the process for developing, deploying, and continuously
improving them is more complex compared to more traditional software,
such as a web service or a mobile application. Continuous Delivery for
Machine Learning (CD4ML) is the discipline of bringing Continuous
Delivery principles and practices to Machine Learning applications. In
this talk we will share our industry experiences implementing CD4ML,
introduce its technical components, and explore what future challenges
need to be solved.
----------------------------------------------------------
Thursday, June 24, 2021
Speaker: Yingnong Dang, Principal Data Scientist Manager in Microsoft Azure
Title: AIOps: From Research Innovations to Industrial Adoptions
Date/time: June 24, 2021, 12:00pm-1:00pm EDT
Registration link:
https://www.eventbrite.ca/e/semla-2021-tickets-154320267073
Abstract:
The scale and complexity of cloud computing has been ever-increasing.
This brings challenges on effectively building and managing cloud
computing systems that are highly efficient and reliable, enable high
customer satisfaction, and achieve high engineering productivity. In
this talk, I will first share an AIOps vision of infusing AI into the
cloud computing platform and DevOps process. I will then share a few
AIOps efforts in Microsoft Azure to demonstrate how an AIOps solution
can be built and adopted in industrial settings. Specifically, I will
share how Azure uses intelligent anomaly detection and correlation for
safeguarding the rollouts of hundreds of component payloads to millions
of machines spreading in 60+ Azure regions across five continents
(project Gandalf safe deployment). I will also share how we built a
resilient mechanism for Azure against failures by employing ML-based
prediction and an online learning mechanism (project Narya). I will then
talk about a few open challenges on cloud computing that need more AIOps
research and innovations.
----------------------------------------------------------
Thursday, July 1, 2021
Speaker: Grace Lewis, Principal Researcher at CMU Software Engineering
Institute
Title: Architecting ML-Enabled Systems
Date/time: July 1, 2021, 12:00pm-1:00pm EDT
Registration link:
https://www.eventbrite.ca/e/semla-2021-tickets-154320509799
Abstract:
Developing software systems that contain machine learning (ML)
components requires an end-to-end perspective that considers the unique
life cycle of these components — from data acquisition to model training
to model deployment and evolution. While there is an understanding that
ML components in the end are software components, there are some
characteristics of ML components that bring challenges to software
architecture and design activities, such as data-dependent behavior,
drift over time, and timely capture of ground truth to inform
retraining. The goal of this talk is to highlight some of these
challenges, along with proposed practices and remaining gaps for
successfully architecting ML-enabled systems.
=================================
Organizers: https://semla.polymtl.ca/organizers/
Follow SEMLA 2020 on:
- Twitter: @SEMLA_sym
- Facebook: @SEMLA_Symposium
--
Foutse Khomh, ing., Ph.D.
Professeur titulaire / Full Professor of Software Engineering
Titulaire de la Chaire de recherche FRQ-IVADO en assurance qualité des logiciels d'apprentissage automatique
FRQ-IVADO Research Chair on Software Quality Assurance for Machine Learning Applications
SWAT Lab., Mila - Quebec AI Institute, Polytechnique Montréal 1-514-340-4711 #4233 (Tél. / Phone)
C.P. 6079, succ. Centre-Ville 1-514-340-4657 (Téléc. / Fax)
Montréal, QC, H3C 3A7, Canada www.khomh.net
--
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