Web Directions ai 2018 Technology/Business/Design of AI

How do we ethical use AI in product design? In this keynote, Caroline Sinders will outline design methodologies, suggestions, use cases, and real life examples for creating more transparent and equitable AI for product design. The future is going to be weird but it doesn't have to be broken, especially for design that touches the lives of everyday users.

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New technologies and the algorithms that reside within them have become the governing bodies of the world. These systems shape the way millions, if not billions of people around the globe behave, think, and operate as a global society, making those creating these systems the modern government representatives to their user base of constituents.

This talk will discuss the power that resides within these systems, why regulation has become a necessary part of the future, and how we can create regulation that balances consumer safety with economic success.

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“Conversation Design” is the new frontier in UX right now, but what exactly does it mean? What have we learnt so far? And what are our UX challenges as we design and adapt user interfaces to be led by conversational interactions?

Amy Cleary will outline some key principles in Conversation Design, drawn from her own experience researching and designing start-up to enterprise level chatbots, as well as from reviewing conventional research in the field.

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Modern applications are increasingly using A.I. and machine learning to drive important parts of their functionality. While there has been significant progress on improving the raw algorithms powering these systems there has been little thought put into *how* they should be used within applications.

In this talk, Nick will show examples from 4+ years experience in running A.I. driven products of the different concerns one needs to consider when integrating these tools into applications.

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Intelligent Agents like Google Assistant, Siri and Alexa are becoming more and more prevalent in a range of products we use, from our mobile, to our car, to our home. What’s the difference between them and more importantly what’s the difference in the relationship that you can have with them. How do you design for the personality of the Agent and the services that your interacting with.

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This talk is around balancing innovation & cool new tech with actual business problems and actual results. This is from multiple lessons learning in the industry. Why engaging the business and running understanding workshops to take business stakeholders on the journey can be the most effect way to create value from AI projects.

You'd be surprised how many projects have no actual outcomes for business!

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Let's explore which industries are likely to adopt such NLG techniques and in what ways can NLG help in business intelligence applications in the near future.

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Due to the hype in the media recently around the recent advances in Deep Learning, machine learning & Ai has been touted about with images of terminator and a doomsday scenario or, as a panacea that can be used to solve any problem - and I believe there is currently a large misunderstanding of what machine learning is & what it can do for your business.

The giants such as Google, Amazon & others, have a firm understanding of what Data Science, Machine Learning & Ai can do to empower their businesses. So do startups, working with very specific machine learning algorithms to solve new problems. However, I believe there is a massive gap “in the middle” where a lot of companies that are not yet familiar with machine learning tech, could benefit immensely from Data Science, Machine Learning & Ai and use it to improve their business systems.

In this talk Paul, co-founder of SigmoidOne and the Sydney Machine Learning meetup group will:

• demystify what machine learning is capable of in 2017,
• Introduce a couple of easy to understand core concepts that can
• Teach you how to identify “machine learning addressable” problems within your business that you can start working on to improve your business today.

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Enterprises are clearly recognizing the value associated with incorporating AI into their business processes. As large companies have increasingly “gone digital,” they have accumulated vast amounts of process, operational, and transactional data sets, which they can leverage to wring out more efficiency, productivity, and cost savings.

Much of the success of AI is due to the fact that most tasks currently delegated to AI technology are data-driven and therefore easily measured or benchmarked. When AI technology is deployed, even during a small pilot program, the benefits can quickly be demonstrated and proven by looking at the performance data.Let's take a look at some of AI solutions we have implemented for our enterprise customers and explore tangible results and values attained.

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