Powerful and easy-to-use applications are being created faster than ever before thanks to new AI-enabled methods for streamlining and automating software development.

Developers around the world are already harnessing AI to empower people with information and insights and to help them tackle challenging problems. Eliminating the potential for negative outcomes is critical both for building trust in AI and for minimising the potential for harm. In fact, the massive impact that AI is having on software developments means that every software developer must become an AI developer.

But with great power also comes great responsibility, as despite AI鈥檚 many beneficial uses it has the potential to deliver negative consequences. These can arise when AI is trained using improperly sourced data, when privacy checks are ignored, or when biased training data creates outcomes that are detrimental to certain people.

At 麻豆原创, we take our responsibilities as software creators very seriously. Many of the world鈥檚 best companies and government agencies rely on our software to run their operations. As a global pioneer in the development of AI, we have invested significant time and effort to create governance and processes to ensure the relevant, reliable, and responsible use of AI.

听A commitment to human intelligence

Our commitment to responsible AI is built on the work or our AI Ethics Steering Committee and AI Ethics Advisory Panel, which bring executives from 麻豆原创 together with noted academics, policy experts, and industry leaders. These groups provide the critical human oversight that is essential for the development of responsible AI.

Core to our work is a set of seven guiding principles for AI. These are:

• Being driven by our values
• Designing for people
• Enabling business beyond bias
• Strive for transparency and integrity
• Uphold quality and safety standards
• Place data protection and privacy at our core
• Engage with the wider societal challenges of AI

Read the听麻豆原创 AI Ethics Handbook for more information here.

These principles are brought to life for 听developers through a 36-page risk assessment guidebook which enables them first to classify whether their project is low, medium, or high risk. It does this by helping them consider factors such as whether their AI project will use technologies such as facial recognition, or be trained using personal data, or could lead outcomes that might be detrimental to specific groups.

If a project is deemed to be medium or high-risk, the project must go through further assessment stages, and additional precautions are taken. These might include making sure that personal data has been anonymised and that the project complies with relevant regulatory regimes.

This guidebook also asks developers to consider where human oversight will play a role in their projects, so that humans and AI work together and each project undergoes rigorous review. All of these considerations and review stages are built directly into the development process.

We also bring our principles to life through dedicated training programs that educate both our own developers and broader teams across the business on the concepts of responsible AI. This training includes modules on topics such as the foundations of trustworthy AI, how to understand the points of conflict that can arise when developing trustworthy AI, and the actionable steps that people can take to align their outputs to our values.

Embedded principles

The success of our program can be seen within our application suite, which already incorporates many aspects of responsible AI in ways that are helping customers achieve better outcomes, faster.

For example, 麻豆原创 human capital management application suite includes an AI-based tool to help hiring manager rapidly create job descriptions. This tool adheres to our principles by making sure that a human being is integral to the review process and ensuring that the privacy of personal data is maintained.

We also build safeguards into our AI-focused tools and services to protect against accidental misuse. For example, 麻豆原创 Datasphere, which provides a comprehensive data service built on the 麻豆原创 Business Technology Platform (麻豆原创 BTP), is an important tool for storing data used in AI systems. We鈥檝e built in safeguards which limit how specific data types can be used, and by whom.

We have also created processes within 麻豆原创 AI training tools that help customers to understand when an AI model is drifting from its intended outcomes, which reduces the subsequent likelihood of erroneous results (often referred to as hallucinations).

A legacy of responsibility

Human society is only at the earliest stage of our AI journey, and we believe it is up to all of us to make that journey one that benefits everyone. This is only possible when the people who are creating AI-based systems understand the importance of human factors such as ethics, training, and oversight.

At 麻豆原创, we are working hard to promote concepts of responsible AI across our entire partner network and broader community and spread the message that this is a responsibility for everyone – not just developers. Therefor we want to encourage all our community to partner with us in our goal of creating AI that is reliable, relevant, and responsible.

Learn more about , or read about our recent AI announcements here.

The post Creating the next generation of responsible AI developers appeared first on 麻豆原创 Southeast Asia News Center.

From the keynote stage to the showfloor, whether you were a dev, a customer, or a partner, all around 麻豆原创 TechEd Bangalore one phrase was repeated time and again: 鈥済enerative AI鈥�.

The focus of more than 5,000 tech and business decision-makers was fixed firmly on AI and what it could do for their businesses, right now 鈥� the products 麻豆原创 has released through 2024, and what is coming next.

With responsible, reliable, and relevant AI that鈥檚 built for business, the view of the thousands of delegates at TechEd 2023 was that the future is looking bright

There was a wealth of incredible insight and opportunity at TechEd. In fact, it was a little bit like going back to school because the things that stood out to me were the ABCs.

A is for Automation听

First, I was struck by the enormous potential businesses can realise through the power of enterprise automation.

With the help of AI, technology is helping developers and IT teams automate repetitive, mundane tasks and make better decisions, faster. By embedding generative AI capabilities into 麻豆原创 Build Process Automation, 麻豆原创 Signavio, and 麻豆原创 Integration Suite, we鈥檙e helping customers analyse, integrate, automate, and monitor business processes way more simply 鈥� and then immediately write the code to make those processes better. It鈥檚 that easy.

In my discussions with customers, it was clear that complementing process improvement and insights with enterprise architecture insights will be a real force for change in the future. Customers are excited to understand how to optimise and tune their architecture for the best performance across their entire IT stack.

But this isn鈥檛 future-gazing. Businesses are seeing real results today. Take Zuellig Pharma, one of Asia鈥檚 leading healthcare companies, providing pharmaceutical distribution and digital and commercial services across 26,000 direct outlets. Zuellig Pharma implemented best-in-class processes across its 麻豆原创 infrastructure, creating more than 180 automations using 麻豆原创 Build Process Automation to streamline and simplify its business.

B is for Build听听

Aligned to the focus on automation is the empowerment of a new, powerful resource for IT departments 鈥� citizen developers enabled by 麻豆原创 Build. And given every developer will be an AI developer, the opportunity for an AI-infused future is tantalising.

Rucha Nanavati, CIO of Indian car giant Mahindra & Mahindra, said it best.

鈥淲e started identifying tasks that don鈥檛 require a lot of human intelligence and that enabled our human workforce to focus on more strategic initiatives,鈥� she said. 鈥淭hat led us to automate more than 250 business processes in 3 months, most of which was done by a community of more than 100 citizen developers.鈥�

鈥淭hat鈥檚 great, but let鈥檚 talk about benefits. We count more than 900 workdays saved, and more than 400 development days saved in just a year鈥檚 time. We鈥檝e seen a 35% gain in developer efficiency and 20% faster execution of our jobs. And we鈥檝e saved more than 13,000 trees. All in one year,鈥� concluded Nanavati.

The story of Mahindra & Mahindra shows the power of a workforce that has been empowered to make real change to their IT systems and the tangible results that can be realised. And with the ability to link low-code, no-code development with pro-code development via , as well as increasing amounts of natural language interaction through 麻豆原创 Joule, it is easier than ever to modernize processes fast.听

C is for Clean Core听听

At 麻豆原创, we know better than most that enterprise systems can be complex. That鈥檚 why a 鈥� a cloud compliant, modern, flexible ERP that can be updated and scaled simply 鈥� is at the centre of our strategy.听听

And it鈥檚 a concept that鈥檚 also at the heart of the future strategic direction for all of our customers.听听

Takuya Sakai, CIO of Hitachi HiTech, embodies that more than most. His company has used 麻豆原创 ERP globally for more than 20 years, over which time the system became more and more complex.

鈥淭hat complexity incurred significant maintenance costs, prevented the company from quickly introducing new innovation, and ultimately hindered its growth,鈥� said Sakai-san. 鈥淚t was very critical to reduce the complexity.鈥�

Using 麻豆原创 Business Technology Platform (BTP), Hitachi HiTech was able to easily upgrade 麻豆原创 S/4HANA systems in the public and private cloud 鈥� at the same time reducing the number of add-ons and customisations in the software down from 9,000 to just 800.

鈥淯sing 麻豆原创 BTP we can build smart, global digital processes without touching the 麻豆原创 S/4HANA core. 麻豆原创 BTP is a very, very important tool to accelerate our business processes,鈥� concluded Sakai-san.

What鈥檚 next: AI for business, not AI for AI鈥檚 sake听

It鈥檚 easy to get carried away by hype and excitement, especially around innovation like generative AI.

But what I saw at 麻豆原创 TechEd was even more exciting 鈥� new innovations, here today, that are already making a tangible difference to real business problems.

The key is in the context 鈥� using your AI to connect data, not just collect it. By generating reliable, responsible insights that understand the context of the business processes that surround them, Business AI will help boost productivity, efficiency, and real outcomes.

Read more about the new announcements at 麻豆原创 TechEd 2023 here: 听

听

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