25 Apr ContactEngine Invited to Speak at Imperial College London about AI Data Transparency
25 April 2018
London, UK: ContactEngine, the market leader in conversation technology, will speak today at Imperial College London’s Explain AI Workshop about data transparency and explainability within artificial intelligence amid the upcoming EU General Data Protection Regulation (GDPR). The Explain AI Workshop will bring together researchers and industry experts to discuss current work around the explanation of AI. ContactEngine is also sponsoring the event, which will feature talks from DeepMind (Google), Fujitsu and University College London, and presentations from Imperial College London’s scientific community.
Francesca Toni, Professor in Computational Logic at Imperial College London said: “Given the ever-increasing integration of AI techniques into everyday systems used by experts and non-experts alike, the need for transparency and explainability in AI has become a pressing issue. The focus of the workshop is explanation: how do we make AI methods transparent?”
ContactEngine is a cloud-hosted conversation management platform that uses machine learning and natural language understanding to engage customers in fully automated and personalised conversations via the customer’s preferred communication channel (SMS, email, phone call, app etc.). ContactEngine will speak to its expertise in AI and benefiting customers in connection with the GDPR data privacy implementations on 25 May.
ContactEngine’s CEO, Dr. Mark K. Smith, commented: “ContactEngine is designed for the customer. Our mission is to create perfect customer journeys based on personalised, automated communication. AI is what helps us achieve that. It analyses customer behaviour to identify the right channel, the right words and the right time for clients to connect with their customers, constantly improving the customer experience. We look forward to explaining more on AI at the Imperial College workshop.”
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For more information, visit: https://www.doc.ic.ac.uk/~afr114/explainAI/index.html