If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This looks like a ton of special sauce, right? Turns out it isn't really all that much. Here's what we got for free from our existing build/deploy tooling: Furthermore, here's what we got for free with SageMaker, instead of using just another general compute cloud like AWS Batch: Finally, note that we essentially use Github comments as the first GUI for the data scientist – which absolves us from having to build an admin tool right away. Extending this, we could probably push notifications about the training job to Slack, buying even more time before we need to build and maintain a custom admin interface. Leveraging these great external – and internal – tools is how we applied our guiding principle and managed to build the platform with just 3 engineers.
Properly prepared data collects a lot of technical metadata describing the form and content of data that a business glossary links to terminology business users will understand. Lineage involves knowing not just where data came from but also whether it came directly from a source or passed through a process, system or application before analysis. The data lineage aspects of a business glossary supports analytics by providing an audit trail for post-decision defenses and post-outcome accountability. Artificial intelligence (AI) applications are driven by analytics that require massive amounts of high-quality data to achieve their goals. A business glossary improves the quality of data by augmenting data with the tacit knowledge of users who understand what the 1's and 0's mean in the ABCs of the business.
As such, even though these technologies bring huge potential and opportunities, they still need to be closely monitored. The University of New South Wales Research Ethics and Compliance Support Director Dr Ted Rohr told HITNA that issues around ethics arise when healthcare access data from medical records for research, for example. "Ethics is all about deciding whether the use of technology is appropriate and is used for public good. For example, AI has its positives, but it can be misused. So, having an ethical framework allows the proper use of medical databases for research and experiments with patients using devices," he said.
The AI revolution has the promise to unlock boundless potential for businesses: from better products and services, to faster innovation and unimaginable leaps in productivity. But, like all great technological advancements, AI also has the potential to create numerous economic, political and social challenges, depending upon how it is used and implemented. Because of that, the use of AI technology needs to be governed by clear rules of ethics -- defined at the outset of this new era, instead of later on, when abuses or ill-considered practices could be far more difficult to control. This is not the first time society has been at a crossroads where we face new technological powers that can serve great and worthy purposes or be abused to support some very bad ones. Yet one thing is clear and remains in our power: artificial intelligence, will never substitute for human wisdom or moral responsibility.
SAP has become the first European technology company to create an external artificial intelligence (AI) ethics advisory panel, with representatives from academia, politics and industry. The panel will ensure the adoption of the new AI guiding principles also announced by the vendor in collaboration with the AI steering committee at SAP, a group of SAP executives from development, strategy and human resources. "SAP considers the ethical use of data a core value," said Luka Mucic, chief financial officer and member of the Executive Board of SAP SE. "We want to create software that enables the intelligent enterprise and actually improves people's lives. Such principles will serve as the basis to make AI a technology that augments human talent." SAP's guiding principles highlight core values around transparency, integrity, quality and safety in the use of AI.
SAP SE (NYSE: SAP) today announced its guiding principles for artificial intelligence (AI) and its creation of an external AI ethics advisory panel – the first European technology company to do so. The panel, comprised of experts from academia, politics and industry, will ensure the adoption of the principles and further develop them in collaboration with the AI steering committee at SAP, a group of SAP executives from development, strategy and human resources. The new guidelines, the external panel and the internal committee aim to ensure that the AI capabilities supported by SAP Leonardo Machine Learning capabilities are used to maintain integrity and trust in all solutions. As the market leader in enterprise technology that touches 77 percent of the world's transaction revenue and serves more than 400,000 customers worldwide, SAP solutions and applications impact the lives of billions of people daily. "SAP considers the ethical use of data a core value," said Luka Mucic, chief financial officer and member of the Executive Board of SAP Se. "We want to create software that enables the intelligent enterprise and actually improves people's lives.
SAP has released its guiding principles for artificial intelligence (AI). Recognizing the significant impact of AI on people, our customers, and wider society, SAP designed these guiding principles to steer the development and deployment of our AI software to help the world run better and improve people's lives. For us, these guidelines are a commitment to move beyond what is legally required and to begin a deep and continuous engagement with the wider ethical and socioeconomic challenges of AI. We look forward to expanding our conversations with customers, partners, employees, legislative bodies, and civil society; and to making our guiding principles an evolving reflection on these discussions and the ever-changing technological landscape. We recognize that, like with any technology, there is scope for AI to be used in ways that are not aligned with these guiding principles and the operational guidelines we are developing.
Artificial intelligence (AI) technologies--and the data driven business models underpinning them--are disrupting how we live, interact, work, do business, and govern. The economic, social and environmental benefits could be significant, for example in the realms of medical research, urban design, fair employment practices, political participation, public service delivery. But evidence is mounting about the potential negative consequences for society and individuals. These include the erosion of privacy, online hate speech, and the distortion of political engagement. They also include amplifying socially embedded discrimination where algorithms based on bias training data are used in criminal sentencing or job advertising and recruitment.
Artificial Intelligence (AI) continues to drive the technology discussion of numerous organisations. Many of our clients want AI solutions, but first want to know exactly what it is, how to integrate it into their existing technology stack, and what use cases demonstrate the most value. If you still cringe at the first step and thought of defining AI in your organisation, don't worry--you are not alone. The most common questions I continue to get asked, as a Gartner analyst researching AI, is "what should AI mean to my organisation, and how should we define it?" So let me help, by offering three key insights and guiding principles that offers CIOs and technical professionals an alternative perspective that leads to a greater path of delivering value from AI to their organisation.