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Forbes
26-06-2025
- Business
- Forbes
The Rise Of False AI Insights: When More Data Means More Problems
Sometimes AI also generates false insights, providing an answer based on real data, but data that is ... More outdated, incomplete or inaccurate. Apple found itself in hot water when news broke that the Apple Card was offering lower credit limits to women, regardless of their financial profiles. The fault lies with the AI algorithm used to analyze creditworthiness; the training data for the algorithm included historical lending data that reflected gendered biases. The lesson here is straightforward: AI makes mistakes. Sometimes AI hallucinates, filling in gaps in data to provide a 'made up' answer—a phenomenon where the model generates plausible but incorrect information. But sometimes AI also generates misinformation and false insights. It provides an answer based on real data, but data that is outdated, incomplete or inaccurate. For example, say you ask AI to pull average salaries for a role at your company. For some reason, the 2020 salary document was opened more recently than the document for 2024. The AI tool thinks the 2020 document is the most relevant, so it uses that data to provide an answer. It's a false AI insight—AI provided an answer based on real data, just not the correct data. As leaders increasingly turn to AI for help with data-driven decision-making, it's important to understand how false insights occur, how to prevent them and what this means for data governance. How Does Too Much Data Lead To False AI Insights? It's no secret that many organizations are drowning in data. On average, organizations leverage nearly 900 apps, with each modern business application collecting and running on a staggering amount of data. This creates a critical challenge: AI requires masses of clean data to produce trustworthy, valuable results. Companies certainly have the volume of necessary data. But where most organizations fall short is in the quality of their data. It's impossible to clean up all their data and properly govern each data point—there's simply too much of it. Consider the possibilities for fake insights from AI when employees start using a tool like Microsoft Copilot. Copilot scans all the documents across the entire system for answers to questions, crafting a response based on what seems relevant. It's not always right. Copilot could pull data from an outdated document from a long-gone employee—not exactly a relevant or trusted source of information. What's more, with new tools such as Microsoft Fabric, a cloud-based, end-to-end data analytics platform, employees are more empowered than ever before to access and act on data. While this creates massive opportunities for organizations, it also multiplies the potential for exposing AI to ungoverned, unmanaged and inaccurate data. It's a catch-22. Governing every piece of data isn't feasible but letting AI access ungoverned data leads to unreliable results. And restricting AI to only well-governed data may limit its usefulness. So what's the solution? How can leaders harness the power of AI and ensure AI doesn't just produce misleading insights? What's needed is a new mindset around governance. Prevent AI Misinformation With A New Output Governance Mindset The age of AI requires a new governance mindset. What's out: governing all the individual data points. What's in: Governing the outputs of AI tools through end-to-end testing strategies. This change in approach will allow organizations to encourage innovation and take advantage of AI while also mitigating the risks of fake insights leading to poor data-driven decision making. Big picture, this new governance framework allows teams to access a broad array of data—including raw or ungoverned data—to build automation tools. But before the tool is brought to production, it must go through a governance checkpoint to evaluate the model and its outputs using standard test cases. The scale and speed with which these innovations occur requires that the testing framework leverage automation to keep up. Skipping this governance checkpoint essentially means letting people create powerful and untested tools for decision making, which could be disastrous to an organization's future success. In addition to a governance checkpoint, each AI tool should be closely monitored during its first 90 days of deployment. This period requires proactive monitoring, with a plan to transition to reactive monitoring once the team gains confidence in the tool's performance. Proactive monitoring involves direct human oversight—reviewing logs, evaluating test cases and using AI-based guardrails to observe the tool's behavior in real time. Once the tool has demonstrated reliability, the team can shift to reactive monitoring, which relies on other AI systems to detect anomalies and trigger alerts when potentially unacceptable behavior occurs. Good output governance means using AI to help govern AI. Think of it like this: the AI doing the actual work—like analytics—is the adult in the room, capable of complex reasoning. The AIs that monitor it are more like kids: they don't always get the big picture, but they're great at shouting, 'Hey! That's not okay!' when something clearly breaks the rules. Another tactic to prevent AI misinformation and inspire confidence in the output from AI is to require AI tools to include annotations in their responses. With every factual question an employee asks of an AI tool, it should list where it's pulling the data from. Employees can quickly scan the annotations and decide if the data sources are trustworthy and make sense. (Needless to say, annotations are most appropriate for AI tools intended for internal use.) AI requires masses of data to work correctly. Organizations have no shortage of data, but most struggle applying data governance to their thousands upon thousands of data points. The solution isn't to lock data away or just let AI loose on ungoverned data. Rather, leaders need to reconsider their governance mindset, putting in place a robust end-to-end testing strategy for any new AI tools to ensure the outputs are accurate and decrease the likelihood of AI producing false insights, leading to poor decision making. By shifting their mindset from data governance to output governance, organizations can unlock AI's potential—without falling victim to AI misinformation.
Business Wire
03-06-2025
- Business
- Business Wire
DoiT Appoints Amit Kinha as Field Chief Technology Officer
SANTA CLARA, Calif.--(BUSINESS WIRE)-- DoiT, a global leader in enterprise-grade FinOps and cloud financial management, today announced the appointment of Amit Kinha as field chief technology officer (Field CTO). In this role, Kinha will guide the DoiT Cloud Intelligence™ vision, roadmap and champion FinOps best practices across the industry. His leadership will ensure that FinOps practitioners and business leaders alike have the actionable insights they need to extract maximum value from every cloud workload. Kinha joins from Citigroup, where he was director of cloud FinOps, leading product and engineering efforts to build in-house FinOps tooling, optimize multi-cloud spend and shape the company's broader cloud strategy. Prior to Citigroup, he spent seven years at Goldman Sachs as a software engineer, where he helped deliver flagship projects, including the Apple Card and Marcus. 'Amit possesses formidable FinOps experience, along with a vision that anticipates and ushers in the future of cloud platforms,' said Vadim Solovey, chief executive officer at DoiT. 'This is the type of world-class talent and expertise driving our technology development. As we move forward, we're confident Amit's leadership will ensure DoiT remains out front in bringing the most effective FinOps tools to market.' An active force in the global FinOps community, Kinha has spoken at FinOps Foundation events, including the NYC Roadshow and FinOps X. He also serves as a FinOps Ambassador and contributes to the evolution of the FinOps FOCUS standard as a member of its Steering Committee. 'FinOps isn't just about cost anymore—it's about control, speed and unlocking smarter decisions at scale,' said Kinha. 'DoiT is rewriting the rules of what's possible in cloud financial management. I'm excited to help shape a platform that doesn't just react to cloud spend—it predicts, governs and elevates cloud strategy into a business advantage.' The DoiT Cloud Intelligence platform was built from the ground up to address the complexities and demands of the Cloud+ era—where mere cost visibility and analytics for cloud spend alone are no longer sufficient, and true efficiency requires understanding the intent and resource behind any workload, managing its risks and enabling action at scale. The DoiT platform enables FinOps-focused organizations to thrive in the Cloud+ era. It is also certified by the FinOps Foundation, the highest recognition offered by the organization. To learn more, please visit About DoiT DoiT is a global leader with its DoiT Cloud Intelligence™ platform, providing intent-aware FinOps solutions that help businesses maximize the impact of their cloud investments. With deep expertise in AWS, Google Cloud and Azure, DoiT Cloud Intelligence empowers to connect every dollar spent to the goals of each workload, go beyond surface metrics to uncover the root causes of inefficiency and close the loop with engineering teams to drive real optimization. With full-stack telemetry and contextualized insights, DoiT enables smarter spending, faster innovation and greater business outcomes.
Yahoo
03-06-2025
- Business
- Yahoo
DoiT Appoints Amit Kinha as Field Chief Technology Officer
FinOps visionary to drive next-gen capabilities for maximizing cloud investments SANTA CLARA, Calif., June 03, 2025--(BUSINESS WIRE)--DoiT, a global leader in enterprise-grade FinOps and cloud financial management, today announced the appointment of Amit Kinha as field chief technology officer (Field CTO). In this role, Kinha will guide the DoiT Cloud Intelligence™ vision, roadmap and champion FinOps best practices across the industry. His leadership will ensure that FinOps practitioners and business leaders alike have the actionable insights they need to extract maximum value from every cloud workload. Kinha joins from Citigroup, where he was director of cloud FinOps, leading product and engineering efforts to build in-house FinOps tooling, optimize multi-cloud spend and shape the company's broader cloud strategy. Prior to Citigroup, he spent seven years at Goldman Sachs as a software engineer, where he helped deliver flagship projects, including the Apple Card and Marcus. "Amit possesses formidable FinOps experience, along with a vision that anticipates and ushers in the future of cloud platforms," said Vadim Solovey, chief executive officer at DoiT. "This is the type of world-class talent and expertise driving our technology development. As we move forward, we're confident Amit's leadership will ensure DoiT remains out front in bringing the most effective FinOps tools to market." An active force in the global FinOps community, Kinha has spoken at FinOps Foundation events, including the NYC Roadshow and FinOps X. He also serves as a FinOps Ambassador and contributes to the evolution of the FinOps FOCUS standard as a member of its Steering Committee. "FinOps isn't just about cost anymore—it's about control, speed and unlocking smarter decisions at scale," said Kinha. "DoiT is rewriting the rules of what's possible in cloud financial management. I'm excited to help shape a platform that doesn't just react to cloud spend—it predicts, governs and elevates cloud strategy into a business advantage." The DoiT Cloud Intelligence platform was built from the ground up to address the complexities and demands of the Cloud+ era—where mere cost visibility and analytics for cloud spend alone are no longer sufficient, and true efficiency requires understanding the intent and resource behind any workload, managing its risks and enabling action at scale. The DoiT platform enables FinOps-focused organizations to thrive in the Cloud+ era. It is also certified by the FinOps Foundation, the highest recognition offered by the organization. To learn more, please visit About DoiT DoiT is a global leader with its DoiT Cloud Intelligence™ platform, providing intent-aware FinOps solutions that help businesses maximize the impact of their cloud investments. With deep expertise in AWS, Google Cloud and Azure, DoiT Cloud Intelligence empowers to connect every dollar spent to the goals of each workload, go beyond surface metrics to uncover the root causes of inefficiency and close the loop with engineering teams to drive real optimization. With full-stack telemetry and contextualized insights, DoiT enables smarter spending, faster innovation and greater business outcomes. View source version on Contacts Metis Communicationsdoit@
GSM Arena
29-05-2025
- Business
- GSM Arena
Apple Card gets another cut on interest rate
Apple Card is a banking service for Apple users in the United States. It has a Savings feature, allowing customers to earn interest on cashback deals, and the rate was 4.15% when introduced. The rate changed several times over time - in March, it was 3.75%, and today, it is reduced to 3.65%, its lowest since the service was introduced. Apple Card The interest rate matches that Goldman Sachs offers through its savings account. Apple is the main partner for this banking service. The 3.65% percentage was adjusted based on overall economic conditions, and while it is lower than before, it is still drastically higher than the national average interest rate in the United States (the Average Percentage Yield, or APY, is 0.59%). APY is the total rate of return for an interest-bearing account over a one-year period. For Apple customers, the sum is accumulated through cashback programs—1% on all purchases, 2% if they are through Apple Pay, 3% on the Apple Store, and partners like Uber or T-Mobile. These funds are returned to the Daily Cash account, but they can be transferred to the Savings account, where they'll earn interest over time. The interest is compounded daily, meaning the money grows every day if the user is patient enough. Via
NDTV
17-05-2025
- Business
- NDTV
Apple Pay Down: Global Outage Causes Payment Chaos For Millions
Apple Pay experienced a significant global outage on Friday, May 16, 2025, leaving users unable to make purchases or access funds. The disruption began at approximately 8:14 PM IST and affected related services, including Apple Wallet, Apple Card, and Apple Cash. Apple's System Status page indicated that the issues were resolved by 10:31 PM IST. With over 745 million users worldwide, including more than 60 million in the US, Apple Pay is a cornerstone of the company's digital ecosystem. While Apple did not specify the number of users impacted, it acknowledged that "some users may have experienced an issue with this service." Outage-tracking site DownDetector recorded over 2,000 user reports in the US, with complaints focusing on payment failures and difficulties transferring funds. Frustrated users took to social media platforms to express their concerns and seek information. DownDetector's outage map showed widespread Apple Pay issues in major US cities, including New York City, Los Angeles, and Chicago, as well as smaller-scale outages in the UK and parts of Europe, affecting users' ability to make transactions and access funds. Widespread disruptions were reported across America. Hundreds of Apple Pay users reported issues on DownDetector and social media, with many receiving an error message stating, "Cannot receive payments sent with Apple Cash at this time." "This is the problem with handing everything over to the technocracy. Apps and services run on #ApplePay, and when it goes down... transactions completely stop," commented a user. "Apple's Response? Do you think Apple should be more transparent about outages like this? How quickly should they acknowledge and fix the issue"? wrote another user. 'Apple Pay being down is the ultimate example of why a cashless society is dystopian. Cash must live on so we are free'. wrote a third user on X (formerly known as Twitter).
