GLSEC 2019 Program & Schedule
May 20th, 2019
The Eberhard Center
7:30 AM Check in
8:00 AM Coffee and Light Breakfast
8:45 AM Opening Remarks
Danielle: Conference Chair
9:00 AM - 10:00 AM Featured Speaker
The lessons learned from the past can help us as a society to seize opportunities to learn how to do better, be better, and plan for a better future. The use of artificial intelligence (AI) is becoming a mainstream reality in today’s society, but how should we view this new reality as it relates to the ethics of AI use and the replication of social inequalities in the digital world? How can AI help mitigate or eliminate present and future social challenges in areas such as health care? This presentation will explore the importance of ethics in design and use of AI technologies.
10:00 AM - 10:15 AM | Short Break
10:15 AM - 11:00 AM | Session Talks
Machine learning and artificial intelligence are driving advances across academia and industry. Bridging the gap between academic research and concrete applications is challenging, and yet, ML approaches frequently produce effective solutions to common problems. In this talk, both academic and implementation specific problems are discussed along with reflections from ongoing projects.
Through weird and hilarious anecdotes, learn about things that give machine learning algorithms trouble (recognizing sheep, counting giraffes, telling jokes) - and the implications these have on deploying machine learning algorithms in the real world.
11:00 AM - 11: 15 AM | Short Break
11:15 AM - 12:00 PM | Session Talks
Trying to accurately predict behavior is an interesting business to be in. In a sense, we are all in this business. For economic development organizations, the pot of gold contains the names of companies poised to relocate or expand. Who are they? Where are they? What do they value? This session will include stories from the hunt, thirty years of applying artificial intelligence / data analytics to predicting corporate behavior, wonder about what’s next, and have some fun along the way.
What is subjective data? How does it contribute to the biases present in AI, and how can we use it to create artistic and emotional datasets? In this talk, we'll talk about identifying subjectivity in otherwise “objective” datasets, critically looking at how the datasets were created and what they contain. We'll talk about artisanal data and creating explicitly subjective datasets for artistic purposes, and how to capture abstractions like emotions and other subjective experiences in datasets. Most importantly, we'll discuss how a culture’s current set of values is a type of bias that gets captured in datasets, and how we can avoid bias retention over time.
12:00 PM - 1:15 PM | Lunch
Grab your food and bring it into the Main Room for Rolf’s talk.
12:30 PM - 1:15 PM | Lunch and Community Discussion
This talk relates stories from a number of organizations that have introduced machine learning and what they learned along this path. How have organizations selected machine learning to solve a need? What expectations should you have for an ML project that differ from a typical software engineering project? What kind of investment is ML? How can you iterate on it? How can you set up a data scientist for success in joining an organization?
1:30 PM - 2:30 PM | Session Talks
We all have more data than we can use. How can we help our companies find the right data, make it widely available, and get value from it?
The appliance industry is evolving to deliver more meaningful experiences to the consumer. This is especially true in our Kitchens where consumers are looking for the products to help them with great cooking experiences. The industry is responding by experimenting with using embedded computer vision and AI techniques to provide delightful experiences to consumers. This talk will present the journey that Whirlpool, a leading appliance manufacturer, has embarked on and the progress they have made on this journey.
2:30 PM - 2:45 PM Short Break
2:45 PM - 3:30 PM | Session Talk
Do you know why you come to work every day, or why your team exists? At the beginning of this story I didn't. Answering those questions led to an activation for myself and my team, and at this West Michigan foodservice distributor, we started a journey with aspirations to transform how customers, employees and suppliers interact with us digitally. We named our new digital assistant Gordon Now™ (gordonnow.com) and it started small. Now we're scaling and frequently surprised at the regularity customers engage with Gordon Now and the level of sophistication in those conversations.
Artificial Intelligence can bring joy to everyday life, or alienate users making them feel unimportant. Here's our take on what's working and not, with examples from our ongoing Gordon Now project.
In this session you’ll learn from local Google Cloud subject matter experts exactly how other organizations have adopted machine learning to improve or differentiate their business. Using some of the key uses cases you’ll get some examples of where to start and any gotchas that others have faced. Bring your ideas and you can leave with ways to make them a reality.
3:30 PM - 4:00 PM Afternoon Ice Cream Break
Come and get it! Love's Ice Cream
4:00 PM - 4:45 PM | Featured Speaker
In our data-driven world, sensor and algorithm performance are rapidly increasing and development tools are making it easier to develop detection systems. Even with these advancements, optimizing detection systems can be difficult. To optimize performance, it’s important to understand the sensing system’s signal quality and how it drives algorithm requirements and capabilities. Whether performance improvement involves tuning sensor parameters or adding capability to the algorithm, it is the designer’s responsibility to navigate these relationships and trade-offs.
Using a camera-based detection system as an example, this presentation describes a design approach that allows the designer to iteratively identify the optimal balance between sensor capability and algorithm capability. Viewers will gain an understanding of several high-impact noise sources, methods for evaluation and ways to determine requirements driven by the detection algorithm. Viewers will also learn how datasets enable evaluation of non-obvious noise sources and system performance.
4:50 PM | Wrap up and Closing Discussion
5:00 PM Let's get the party started!
Post Conference Mixer
Grand Rapids Public Museum.
The Grand Rapids Public Museum is a very short walk from the Eberhard Center. There will be food and beverages. Most importantly, interesting people and conversations.