Tag: machine learning

  • Soul in the Machine – Can we avoid the Google Duplex outrage in Conversational AI development?

    Soul in the Machine – Can we avoid the Google Duplex outrage in Conversational AI development?

    This is Part 5 in the Soul in the Machine series. In the Soul in the Machine series, I will be delving into our collective responsibility to ensure that computing systems are treating users fairly and responsibly. Specifically, I will be raising the ethical questions around current trends such as data privacy…

  • Preparing for AI-driven customer experiences

    Preparing for AI-driven customer experiences

    Digital marketers today are caught in the middle of a huge digital transition. Behind them lie the old, slow, and manual methods of creating content, connecting with customers, tracking engagement, and measuring the results. Ahead of them is the promise of the brave new intelligence-enabled world, teeming with possibilities—task automation, massive-scale…

  • Soul in the Machine – Combatting Unconscious Bias

    Soul in the Machine – Combatting Unconscious Bias

    This is Part 4 in the Soul in the Machine series. In the Soul in the Machine series, I will be delving into our collective responsibility to ensure that computing systems are treating users fairly and responsibly. Specifically, I will be raising the ethical questions around current trends such as data privacy…

  • Soul in the Machine – Top AI/ML Orgs and Unconscious Bias

    Soul in the Machine – Top AI/ML Orgs and Unconscious Bias

    This is Part 3 in the Soul in the Machine series. In the Soul in the Machine series, I will be delving into our collective responsibility to ensure that computing systems are treating users fairly and responsibly. Specifically, I will be raising the ethical questions around current trends such as…

  • Continuous Improvement for Customer Engagement

    Continuous Improvement for Customer Engagement

    Sitecore’s Customer Experience Maturity Model has been around for a while and it is still as relevant today as it was when it was first released. The model helps a team to understand where they are right now and where they could possibly be with customer engagement. However, it isn’t…

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