IBM Journey to AI blog

APRIL 11, 2023

In line with this trend, the New York City Council has enacted new regulations requiring organizations to conduct yearly bias audits on automated employment decision-making tools used by HR departments. Our organization is ready to assist companies in becoming data-driven and addressing compliance.

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Unite.AI

DECEMBER 27, 2024

Automated tools such as TensorFlow Data Validation (TFDV) and Great Expectations help enforce schema consistency, detect anomalies, and monitor data drift. Another promising development is the rise of explainable data pipelines. This transparency fosters trust in AI systems by clarifying their foundations.

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Data Quality Data Drift Explainability Big Data 130

AI News

OCTOBER 8, 2024

So we would like to generalise some of these algorithms and then have a system that can more generally extract information grounded in legal reasoning and normative reasoning,” she explains. Kameswaran suggests developing audit tools for advocacy groups to assess AI hiring platforms for potential discrimination.

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IBM Journey to AI blog

MAY 9, 2023

A lack of confidence to operationalize AI Many organizations struggle when adopting AI. According to Gartner , 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted.

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Metadata Explainability Automation Responsible AI 227

Unite.AI

JUNE 18, 2024

This fascinating fusion of creativity and automation, powered by Generative AI , is not a dream anymore; it is reshaping our future in significant ways. Looking further ahead, one critical area of focus is Explainable AI , which aims to make AI decisions transparent and understandable.

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AI Weekly

JUNE 1, 2023

Powered by 1west.com In the News Generative AI may be the next AK-47 At the start of the Cold War, a young man from southern Siberia designed what would become the world’s most ubiquitous assault rifle. With our Automated Business Lending Engine (ABLE), we are here when you are ready to enhance your business with some capital.

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IBM Journey to AI blog

OCTOBER 16, 2023

. “Foundation models make deploying AI significantly more scalable, affordable and efficient.” It’s essential for an enterprise to work with responsible, transparent and explainable AI, which can be challenging to come by in these early days of the technology. ” Are foundation models trustworthy?

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IBM Journey to AI blog

AUGUST 17, 2023

That’s why the US Open will also use watsonx.governance to direct, manage and monitor its AI activities. A new era of scalable enterprise AI Through their longstanding partnership, the IBM and the USTA collaborate to explore new ways to use automation and AI to deliver compelling fan experiences at the US Open.

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Dlabs.ai

JULY 25, 2023

New York City has responded to these concerns by introducing new regulations on using Automated Employment Decision Tools (AEDTs) in 2023. Let’s start by explaining what exactly Automated Employment Decision Tools (AEDTs) are. How can we ensure these technological advances don’t harbor biases or injustices?

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Automation Machine Learning Algorithm Explainability 98

IBM Journey to AI blog

MARCH 4, 2024

Where do you harness gen AI vs. predictive AI vs. AI orchestration? For instance, when automating password change requests, do you need a 175 billion parameter public foundation model, a fine-tuned smaller model, or AI orchestration to call APIs? When should you prompt-tune or fine-tune?

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IBM Journey to AI blog

FEBRUARY 8, 2024

Getting ready for upcoming regulations with IBM IBM watsonx.governance accelerates responsible, transparent and explainable AI workflows IBM® watsonx.governance™ accelerates AI governance, the directing, managing and monitoring of your organization’s AI activities.

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IBM Journey to AI blog

SEPTEMBER 18, 2023

Siloed processes can become integrated by using intelligent workflows, which help enable seamless and automated exchange of financial, informational and physical supply chain data in one distributed network. It can help connect disparate and disconnected manual processes and platforms to a data-driven and connected trade ecosystem.

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IBM Journey to AI blog

AUGUST 12, 2024

The integration of generative AI, particularly LLMs, offers transformative potential to automate compliance processes, detect anomalies, and provide comprehensive insights into regulatory requirements. Financial institutions are prioritizing the integration of AI to address pressing challenges and enhance their competitive edge.

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IBM Journey to AI blog

DECEMBER 4, 2023

IBM watsonx.governance ™, a component of the watsonx™ platform that will be available on December 5 th , helps organizations monitor and govern the entire AI lifecycle. It helps accelerate responsible, transparent and explainable AI workflows.

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Metadata AI AI Explainable AI 228

IBM Journey to AI blog

OCTOBER 12, 2023

Explainable AI — Explainable AI is achieved when an organization can confidently and clearly state what data an AI model used to perform its tasks. Key to explainable AI is the ability to automatically compile information on a model to better explain its analytics decision-making.

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IBM Journey to AI blog

FEBRUARY 8, 2023

It is the process of defining policies and establishing accountability to guide the creation and deployment of AI systems. For many of today’s organizations today, governing AI requires a lot of manual work that include the use of multiple tools, applications and platforms.

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IBM Journey to AI blog

OCTOBER 17, 2024

But what many might not know is how Cognos Analytics has seamlessly integrated artificial intelligence (AI) to revolutionize users’ BI experience. AI in Cognos automates many traditionally manual tasks. Automated metrics creation Even the task of creating metrics and KPIs is simplified.

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Unite.AI

JULY 2, 2024

Administrative automation for education and other industries AI systems classified as high risk are subject to strict compliance requirements, such as establishing a comprehensive risk management framework throughout the AI system’s lifecycle and implementing robust data governance measures.

AI Strategy 162

AI Strategy Explainability AI AI 162

Unite.AI

SEPTEMBER 20, 2024

Its real-time trend analysis, investment evaluations, risk assessments, and automation features empower financial professionals to make informed choices efficiently. Key milestones in this evolution include the advent of algorithmic trading in the late 1980s and early 1990s, where simple algorithms automated trades based on set criteria.

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Unite.AI

DECEMBER 13, 2023

Organizations must showcase how AI-driven decisions are made, making explainable AI models important. AI-Powered Cybersecurity Workforce Training By 2030, an estimated 30% of tasks will be automated using AI technology. Prepare for a new cybersecurity workforce training era as AI enters the scene.

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IBM Journey to AI blog

JULY 17, 2023

While traditional AI approaches provide customers with quick service, they have their limitations. Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. Watsonx.ai

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Unite.AI

OCTOBER 25, 2024

SLK's AI-powered platforms and accelerators are designed to automate and streamline processes, helping businesses reach the market more quickly. In mortgage requisition intake, AI optimizes efficiency by automating the analysis of requisition data, leading to faster processing times.

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Automation Explainability Responsible AI AI Automation 147

Aiiot Talk

JULY 7, 2023

AI can streamline and automate key safety processes such as design, monitoring, testing and more. AI-Powered Predictive Maintenance AI is a powerful tool for improving aircraft safety through predictive analytics. Generative AI can also pose risks for aviation industry applications.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

IBM watsonx.data is a fit-for-purpose data store built on an open lakehouse architecture to scale AI workloads for all of your data, anywhere. IBM watsonx.governance is an end-to-end automated AI lifecycle governance toolkit that is built to enable responsible, transparent and explainable AI workflows.

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IBM Journey to AI blog

AUGUST 9, 2024

Marketing and advertising: Generative AI can design engaging visuals and craft compelling ad and sales copy customized for each target audience. Software development: Code generation tools can speed up the process of writing new code and automate the debugging and testing phases.

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IBM Journey to AI blog

JANUARY 25, 2024

Chamber of Commerce Foundation and IBM explore generative AI’s applications for skills-based hiring How the Titanic helped us think about Explainable AI A Framework to Render AI Principles Actionable Automated AI model governance tools are required to glean important insights about how your AI model is performing.

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IBM Journey to AI blog

AUGUST 11, 2023

MLOps, which stands for machine learning operations, uses automation, continuous integration and continuous delivery/deployment (CI/CD) , and machine learning models to streamline the deployment, monitoring and maintenance of the overall machine learning system. How to use ML to automate the refining process into a cyclical ML process.

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Marktechpost

AUGUST 13, 2024

Integrating AI and human expertise addresses the need for reliable, explainable AI systems while ensuring that technology complements rather than replaces human capabilities. Automated AI Systems handle repetitive tasks within specific domains, like robotic process automation and forest management.

Robotics 106

Robotics Explainability Explainable AI Categorization 106

Unite.AI

SEPTEMBER 13, 2023

Generative AI-powered chatbots could help alleviate much of the workload and preserve overextended patient access teams. On the patient side, generative AI has the potential to improve healthcare providers’ call center services.

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AWS Machine Learning Blog

MARCH 6, 2025

These agents autonomously gather, process, and consolidate data into actionable insights, orchestrating and automating business logic to streamline processes and provide real-time insights.

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Pickl AI

FEBRUARY 17, 2025

Summary: Machine Learning’s key features include automation, which reduces human involvement, and scalability, which handles massive data. Key Features of Machine Learning Machine Learning (ML) is a subfield of AI where computers learn from data without explicit programming.

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Machine Learning Algorithm Explainability Data Quality 52

AWS Machine Learning Blog

NOVEMBER 15, 2024

If you are planning on using automated model evaluation for toxicity, start by defining what constitutes toxic content for your specific application. Automated evaluations come with curated datasets to choose from. Explainability The explainability dimension in responsible AI focuses on understanding and evaluating system outputs.

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Marktechpost

JUNE 9, 2024

Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt to clarify these models by highlighting key ECG features. This approach enhances the interpretability and reliability of ECG classifications, bridging the gap between clinical needs and automated analysis. Check out the Paper.

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Unite.AI

APRIL 22, 2024

With more than 13 million global users, Ada Health exemplifies transparent, explainable AI in healthcare, providing clear insights into the diagnostic process. It enables precise symptom assessment against a database containing 3,600 conditions and over 31,000 ICD-10 codes, encompassing 99.5% of all diagnosable conditions.

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Marktechpost

MAY 12, 2024

It is based on adjustable and explainable AI technology. The technology provides automated, improved machine-learning techniques for fraud identification and proactive enforcement to reduce fraud and block rates. Fina also uses AI-based analytics to give users insights and recommendations for improving their financial strategy.

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Marktechpost

MAY 5, 2024

Existing surveys detail a range of techniques utilized in Explainable AI analyses and their applications within NLP. Circuit analysis identifies interacting components, with recent advances automating circuit discovery and abstracting causal relationships. Recent approaches automate circuit discovery, enhancing interpretability.

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ODSC - Open Data Science

AUGUST 14, 2023

“I still don’t know what AI is” If you’re like my parents and think I work at ChatGPT, then you may have to learn a little bit more about AI. Funny enough, you can use AI to explain AI. And now that you understand what AI is, it’s all about using it, leading to the next point. “No

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