The challenge for organizations today is how to deliver a multi-layered complex system to serve the needs of many and make sure the business will survive and thrive despite everchanging market dynamics. As designers, we often find ourselves solving large-scale, complex problems and leading global transformation programs, which can be challenging. And breakthroughs come from a new way of thinking in transformation. So, we've started with system design! Together with my teams at two separate innovation centers, we've pioneered System Design as a new method of problem-solving to tackle large-scale, complex challenges. We have delivered innovative solutions such as blockchain-based ID systems for the United Nations for ID'less societies or building data-driven, intelligent platforms to eliminate food waste for supermarket chains. System Design Framework combines well-known design thinking and systems thinking to analyze systems collectively, enables the right next actions and shapes the technologies most suitably. In this session, I will share insights on applying System Design Framework to drive innovation and deliver value to organizations.

Nur is design expert in everything about human-centred services and systems. With a deep passion to shape new technologies and deliver value for humanity Nur helps organisations to achieve sustainable transformations and leverage new technologies for better use. She has set up and led award-winning innovation teams in Europe and managed capabilities such as UX, Service Design and System Design. She is the author of the System Design Practice book. Currently, she works with the United Nations’ Accelerator labs and provides training in System Design at multiple universities in Europe.

In this presentation, Adi will share an on-the-ground perspective of what designers can do to get into the weeds and co-create this value. Through stories from personal experience on this journey, she'll bring a view on what it means for a designer to shape the direction of AI at their business, tactically and strategically.

Adi Veerubhotla is a UX Architect in the Data & AI group at IBM. She has been in enterprise design for 10 years, focusing on information exploration and sense-making from business data. For half of that time, she has been designing experiences for and with cutting-edge AI technology. To her, machines are tools to be used for a purpose. Through her education in Computer Science and Human Computer Interaction, she enjoys blending the world of experience design, cognitive psychology and systems thinking to craft responsible systems of value.

Beyond work, she enjoys nature & experimental cooking with vegetarian food, and is learning to view the world again through the curious eyes of a little kid.

As design & product leaders, our shared goal is to bring differentiated value for our customers & companies. This value can be provided by analyzing & predicting outcomes from data. When incubating new products & concepts, it's paramount to think about what design strategies can help curate these data & drive successes for customers.

In this presentation, Sen will discuss how his team within FCAT, which is at the heart of Fidelity's 'innovation engine,' uses design-thinking and data science to incubate new products. This talk will include stories & lessons learned from a product designed, developed & launched at an AI-Incubator. Using examples of iterative product development, Sen will also talk about how using a human-first approach, building trust with users & authentic data-driven experiments helped his team drive the product to success.

Supritam Sen is a Director of Product Management at Fidelity Center for Applied Technology (FCAT). He currently leads multiple cross-functional teams within an AI-Incubator within FCAT. His focus is to assess, test, and scale AI products/concepts that provide value to Fidelity's internal employees & external customers. Over the last few years, his focus has been to incubate products using Design and Data Strategy. He is passionate about investing & finance, and in his free time, he likes to read, watch soccer, and travel to new places. Sen holds an MS. in Computer Science from NC State University and an MBA from Fuqua School of Business (Duke University).

This talk reviews three primary models (Cramer, 2017) of Mixed Methods research design and from those creates a ‘cheat sheet’ model that supports researchers in deciding how and when to incorporate Mixed Methods in their research designs.

Through three different real-world cases we will discuss each model and its application. These examples will showcase how Mixed Methods can be an important factor in influencing many types of impact, from product strategy, audience strategy through to company strategy. Each case discussed will help shine light on the benefits of a particular approach and limitations of mixed methods when applied.

Rina Tambo Jensen is a UX and Product Leader, experienced in managing and scaling teams including design, research and product. Currently leading the talented and diverse Design & UXR team at Chan Zuckerberg Initiative for our Science products. Busy applying human-centered design to our world of scientific tooling, open-source products and new scientific technologies. Previously Director of Design & Product for Mozilla's Open Innovation team.

Measuring design experience and design quality is not easy, but as design's role becomes more blended with technology and business results, the tactical ability to build design's database of measurability is crucial. Here, I would like to present practical, data-based frameworks that provide a differentiation in measuring subjective versus objective aspects of user experience at scale. Design leaders must prepare for the next frontier of maturity in scaling design teams, and data is part of that adventure.

As a design and research leader, Jessa Parette seeks to build intentional experiences and visionary teams. Her career expands over several industries including banking, retail, nonprofits and higher education. Jessa worked her way from an entry level designer to becoming the youngest Head of Design for all of Walmart’s associate digital experience, leading both design and research for national and international products. In her current position as Head of Design Strategy, Systems and Research for Capital One’s auto finance, she builds and leads teams to change banking for good.

In this use case on integrating design, data and AI, I will show how human-centered technology can contribute to the transformation of healthcare. By showing an explorative, first-of-a-kind clinical design trial with bariatric patients and healthcare professionals of the Catharina hospital in the Netherlands, I'll present how patient engagement can be improved by making care more personal and precise. And how we explored different ways to interact more directly and effectively with patients and a multi-disciplinary team of healthcare professionals. By testing an intelligent ecosystem, including sensors and data-trackers we were able to gather data about patient's experience, context and behavior, and I will show how that has led to a better understanding of patient’s needs and new forms of care delivery and future healthcare concepts.

Jos-marien is specialized in UX research for healthcare innovations and in Data-enabled Design where mixed methods are used to collect qualitative and quantitative data, which is input as a creative material for innovation.

In her work, she combines intelligent ecosystems, artificial intelligence and deep user insights into user needs. She loves to work in multi-disciplinary teams with designers, statisticians, data scientists, psychologists, clinicians and patients.

Speculative fiction writer and essayist, William Gibson said: 'The future is already here, it's just not evenly distributed.'

Most of us at this conference would very quickly be able to create a list of currently emerging technologies: non-fungible tokens, the metaverse, blockchain, machine learning, computer vision, artificial intelligence, regenerative agriculture, lab-grown meat, CRISPR, robotics. These technologies have the potential to change everything.

Our job as designers is to find truly compelling value propositions for these technologies in peoples' everyday lives; to apply these technologies to solve real human problems in real human ways.

Designer, PJH, will share his experience of defining the value proposition for a machine learning and computer vision product and how his studio designed the user interface to unleash the power of those technologies.

Paul-Jervis Heath is an award-winning product strategist and designer with almost 25 years of experience. He is Chief Creative Officer and a founding partner of Modern Human, a multidisciplinary design practice and innovation consultancy. Modern Human design products, services and environments that enrich modern life and exists to empower and liberate real people through design.

PJH's highly diverse portfolio of design projects includes dashboards for autonomous vehicles, smart home appliances, intelligent environments, digitally integrated retail stores, publishing services that accelerate the pace of human discovery, geospatial information services to enable conservationists to protect endangered species and augmented reality toys. He has designed libraries, museum exhibits and even a call centre.

Paul Jervis Heath has built design practices within a number of organizations. He is the former Head of Innovation at Cambridge University and has led design at a number of London design firms.

For nearly one thousand years humans have been designing programmatic machines to augment our work and play. Until very recently, those machines were merely tools we wielded. Now we are challenged with a new realm of experience design: dynamic experiences for humans collaborating with artificial intelligence (AI). This is new and exciting work! Identifying and considering the benefits and limitations of these systems is challenging enough. Determining how, and to what extent, they will augment their human partners; what that exchange 'feels' like and how it changes over time; and how we will keep people safe and in control can be intimidating. What new thought paradigms, design approaches, and perhaps even methods are needed? Together we'll explore the implications on UX that these systems have and how we can design human-centered AI.

Carol Smith’s career spans 20 years collaborating on complex problems, focusing on UX research and prototyping, across industries and platforms. She has been leading research to integrate ethics and improve human experiences with artificially intelligent (AI) systems, autonomous vehicles, and other emerging technologies since 2015.

Carol is a Senior Research Scientist in Human-Machine Interaction for the AI Division of Carnegie Mellon University's Software Engineering Institute in Pittsburgh, PA. Carol also teaches courses for CMU's Human-Computer Interaction Institute (HCII). She is an active UX community organizer, served two terms on the UXPA international board, and is an ACM Distinguished Speaker. Carol has an M.S. in HCI from DePaul University.

Large scale aggregating data provides new opportunities to improve healthcare at scale by supporting clinical decision making. Research in Explainable AI has explored ways to improve the legibility of AI models drawn from big data, and the field of UX has developed heuristics and explorations for ways to interact with data. But UX hasn’t developed systematic approaches to interacting with big data, and Explainable AI has focused on the AI model itself, rarely addressing the front end. In this talk, I’ll discuss the difficulties and opportunities at the intersections of those domains, and discuss how to build strategies and organizations to build legible, insightful, and empowering tools.

Jofish Kaye, Ph.D, is Senior Director of Interaction Design & Artificial Intelligence at Anthem Health Platforms. He runs research, design and user experience teams to produce thoughtful and ethical HCI and AI products. His research explores the social, cultural, and technological effects of technology on people, and how people’s decisions, needs, and behaviors can change and improve those technologies. He has served on the ACM Diversity & Inclusion Council, chaired CHI 2016, and has a long running interest in improving diversity, inclusion, and accessibility. He has a Ph.D in Information Science from Cornell and MS and BS degrees from MIT.

Are you trying to understand AI at your organization? Looking for ways to connect with engineers? Hoping to design human-centered AI experiences for users?

This talk will cover:

1. LinkedIn AI and the importance of quality data

2. A framework on how to design human-centered AI experiences

3. Cross-functional workshops that help engineers and other functions understand user perceptions of AI

Carolyn Chang is a Principal User Experience Researcher at LinkedIn. Her current passion areas include: AI, enterprise products, research impact and marketplaces. You’ll likely find her managing ambiguous, horizontal projects. One important hallmark of her work is that stakeholders have a meaningful, fun time learning about users. At home, she tries to manage 2 young kids and have a relaxing fun time.

Christine Liao is a Product Design Lead at LinkedIn. Originally intending to study medicine, she found herself enamored by the creative industry, and found her way to architecture. After a short stint at an architectural firm, she transitioned into UX design.

At LinkedIn, she manages a team focused on helping recruiters search and find candidates, and is passionate about leveraging AI as a way to help people discover candidates they might have otherwise overlooked. In her spare time, she likes baking meticulous things and drawing!

Although people have envisioned the impact of computers on design and engineering since the earliest days of computing, many of our CAD design and engineering tools still, in essence, replicate pre-digital design practices with digital tools. They’re super-paper and super-pencils. We think that the age of such computerized design is rapidly waning, and the age of computational design has finally arrived. We can incorporate data and AI at every stage of a design process (any design process, though our team’s focus is on physical products), from conceptualization to recycling. Computational Design does not automate design practice, it fundamentally transforms design tools, and perhaps the very definition of what it means to design and engineer.

As access to data—and our ability to extract knowledge from it—grows, we see opportunities for organizations to rethink design at a fundamental level. In this talk I will present how we at Accenture Labs approach computational design not from the perspective of building a single tool, nor as optimization, nor automation, but as an evolving set of AI assistants that play different roles across the design process and complement the skills of human designers.

Mike Kuniavsky leads the Digital Experiences team at Accenture Labs. His team works to invent new user-centered products that combine IoT, AI, and smart materials. His current research is centered on AI-powered design assistants and the future of work.