Does your organisation use a Responsible AI?

Assessing Ethical AI Implementation and Impact.

Microsoft Responsible AI

Importance of Responsible AI

The boom in AI innovations means that AI systems are more than ever incorporated into our daily life. Does it always respect our security, privacy and provides transparency and fair treatment? AI systems may, in some cases, cause harm, not just affecting society but also the reputation of organisations and developers of AI systems.

Microsoft Accessible AI Guidelines

Developing a Responsible AI approach presents a difficulty for numerous organizations, prompting Microsoft to establish standardized Responsible AI guidelines accessible for adoption by other companies and machine learning experts.

A Complete AI Lifecycle

These practices cover the entire AI lifecycle, from creation to implementation, and include tools like a Responsible AI impact assessment template that helps users evaluate AI applications, maintain data integrity, and identify potential negative impacts.

AI Accountability Assurance

Microsoft supports AI responsibility by providing tools and research for developers. These include the Responsible AI Dashboard for debugging machine learning models, a feature of Azure Cognitive Services aligned with Responsible AI principles.

AI Accountability Assurance

6 Core Responsible AI principles

These six principles guide AI developers to be responsible and transparent about their AI system's functionality, usage, limitations, and known issues. They help machine learning teams evaluate their development approach, ensuring the AI behaves as intended.

Fairness

Ensure that AI systems do not exhibit unjust or biased behavior, treating all individuals and groups equitably.

Inclusiveness

Incorporate diverse perspectives and avoid exclusion to create AI technologies that benefit and serve a wide range of users.

Safety

Implement measures to prevent harm, both physical and psychological, while deploying AI systems and minimizing risks associated with their operation.

Accountability

Build AI systems that consistently perform as intended, delivering accurate and dependable results across various scenarios.

Reliability

Hold individuals and organizations responsible for the design, development, and consequences of AI systems, including addressing any unintended outcomes.

Transparency

Provide clear and understandable explanations of AI system behavior, decisions, and processes to enhance comprehension and promote trust among users and stakeholders.

AI Case studies

Leveraging smart workflow and automation

Leading Professional Service organisation selling SaaS solutions leveraged Azure OpenAI Services, CharGPT, and machine learning to deliver continuous product innovation. They now apply automation at all levels with embedded generative AI assistant.

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Improvement with Collaborative AI

German power supplier had to go through a long manual process of checking the power line and maintaining it. With new digital solutions, the supplier aims to increase the efficiency and safety of the process.

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Automatic translation of documents

A global automotive conglomerate operates internationally and with the help of Azure AI improved translation efficiency, precision, and cost-effectiveness to meet growing demands and evolving communication needs.

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Pre-Owned Vehicle Market with AI

Becoming the largest retailer of pre-owned vehicles in the United States through the transformation of the used car buying process with AI.

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Scaling Retail Optimization with Azure AI

Usage of Microsoft Azure Automated machine learning to enhance image recognition and drive retail success.

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Death to the tickets

From time entry automation to game-changing efficiency - the journey of transforming customer support.

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Proven competence

Awards & certifications

Success
Microsoft Gold Implementation Partner since 2005

Related service

Microsoft Azure

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Leading platforms for developing and managing business apps, enabling you to take complete control of your data.

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Allnex

Case study

Building a lead automation engine for a major chemical industry company

Allnex

How Actum used Microsoft Power Platform to fully automate lead assignment and data creation in Dynamics 365 using Power Automate, enabling the chemical coating company to retain complete control.

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