Every day, more companies are adding generative artificial intelligence assistants to their products and services. This week, some of the biggest names in software announced integrations and deployments that they say are safe and transparent uses of AI, while a healthcare IT research organization published guidance on automation, ethics and trust.
IBM introduces Watsonx legal protection
To address customer concerns about the use of generative AI, IBM announced it would indemnify its customers against intellectual property claims against IBM-developed Watsonx models.
The company’s standard contractual intellectual property protections for IBM products will apply to its specialized Granite models that apply generative AI to the modalities of language and code, according to the announcement last week.
Customers can develop AI applications using their own data, along with the customer protection provided by IBM’s core models.
IBM also said it would publish its underlying training datasets.
The basic models developed by IBM are trained on business-relevant datasets from the Internet, academic, code, legal and financial fields and are compiled for business use.
“When it comes to the current boom in AI innovation, the companies positioned for success are those equipped with AI technologies that demonstrate success at scale and have built-in guardrails and practices that enable responsible use of them” , says Dinesh Nirmal, senior IBM Software. vice president of products, said in a statement.
On Monday, IBM announced on its website that it is partnering with telemedicine company Ovum Health to scale web- and mobile app-based chat and scheduling solutions on its family-building platform that provides maternity, prenatal and postnatal health care.
IBM has helped Ovum Health create a no-code platform for an AI assistant that uses natural language models, a researcher said. blog post. Ovum then fully integrated Watsonx Assistant into its web interface and iOS app in less than two months
Wolters Kluwer unveils AI Labs
On Tuesday, the Waltham, Massachusetts-based company introduced a new UpToDate integration called AI Labs.
According to Wolters Kluwer Health, more than two million users at more than 44,000 healthcare organizations in 190 countries rely on the clinical decision support system to view more than 650 million topics per year.
“Bringing together the power of UpToDate and generative AI can help increase value for both physicians and patients,” said Greg Samios, president and CEO of clinical effectiveness, in the announcement.
“With this advanced capability, we have an implementation of generative AI that can help physicians make better and more informed decisions to deliver the best care everywhere.”
Dr. Peter Bonis, Chief Medical Officer, said the company has long been integrating AI to synthesize medical literature and physicians’ experience into 12,400 clinical topics.
To help hospitals and healthcare institutions better aggregate data from disparate electronic health records after mergers, Wolters Kluwer has developed a machine learning model to improve the process by mapping laboratory results and other data to standardized LOINC codes.
“We aim to set a standard for the responsible application of generative AI in the complex reality of primary healthcare,” said Bonis.
“The approach they have taken is the right one and I look forward to seeing how it develops,” added Julio Ramirez, chief scientific officer of the Norton Infectious Diseases Institute.
Chilmark offers an industry guide to AI adoption
Also this week, Chilmark Research released its first eBook, “Building Responsible AI in Healthcare: A Journey into Automation, Ethics and Trust.”
The healthcare IT research and consulting firm’s ebook explores how to develop trust in AI technologies and implementation that positively impact patients, healthcare providers, and organizations.
The content includes a combination of the past three years’ public and premium articles and reports, and includes:
- The evolving regulatory landscape and the need for guide rails.
- Emerging best practices for developing and deploying AI.
- AI biases and how to address health equity mandates.
“We are still in the early days of mass adoption, so most use cases are low risk and focused more on administrative and operational use cases,” John Moore, managing partner of Chillmark, said in a statement.
“As overtures are made toward broader adoption for clinical decision support, understanding the limitations of these tools and the need for human interpretation is critical.”
“Organizations will need to have a deep understanding of fairness and equality from a political philosophy or anthropological perspective, develop design expertise relevant to machine learning, and consciously monitor applications throughout their lifecycle to improve and build user and patient trust. retain.” added lead author Dr. Jody Ranck.
Ranck, the company’s senior analyst, has explored state-of-the-art processes for AI bias and risk mitigation and how to develop more reliable machine learning tools for healthcare.
Andrea Fox is editor-in-chief of Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a HIMSS Media publication.