Perspectives from the front

The Data & Trust Alliance, with support from IBM, offers a new series of perspectives with practical insights from businesses earning trust with data and AI.

The era of data and AI has arrived — and with it, practical challenges for the world’s businesses. Taking a wait-and-see approach? You risk missing a historic opportunity to spark innovation. Worse, you may get disrupted by more agile competitors. On the other hand, letting a new technology proliferate haphazardly within your company poses real dangers — both of operational inefficiency and of reputational, and even legal, exposure.

In a new series of perspectives, the Data & Trust Alliance and IBM offer insights from businesses on the front lines of this new era — enterprises that are creating new value and earning trust with data and AI.

Data quality, AI performance and trust

With respect to AI, data quality generally refers to the accuracy, completeness, consistency, timeliness, uniqueness, and validity of a given data set, as well as the data’s fitness for the purpose for which it is being used. But the practical meaning of “high-quality data” in any given context will depend on the needs of the organization and the specific use case involved. Download the Data Quality Perspective here.

Protecting individuals and enterprises through algorithmic safety

Algorithmic safety refers to processes that ensure algorithms don’t produce biased or harmful results. Algorithmic safety practices include evaluating the quality of training data, ensuring that the algorithms are appropriate for the context and purpose for which they’re used, and providing education and training for the people who build and use AI tools. Download the Algorithmic Safety Perspective here.

The urgency of AI governance

AI governance is a system of rules, practices, processes and tools that help an organization use AI in alignment with its values and strategies, address compliance requirements and drive trustworthy performance. Download the AI Governance Perspective here.

Success in the coming era of business will depend on the safe, ethical and responsible use of AI.”

The Data & Trust Alliance, established in September 2020, brings together leading businesses and institutions across multiple industries to learn, develop and adopt responsible data and AI practices.

These perspectives were developed in partnership with IBM, a leading provider of global hybrid cloud and AI, as well as consulting expertise. IBM helps clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. More than 4,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service.