Windows 10: Is AI helpful to Microsoft or harmful?

JaiPam · Mar 16, 2024

The use of AI, in my opinion, is not very Intelligent in a lot of areas, and I don't think it is helpful to Microsoft in the area of generating puzzles to determine authenticity.Unless perhaps, it's what is fed the AI.I do not think asking a user to solve a puzzle 20 times before verification is necessary. Five times at least should be enough to accomplish what is desired. Unless the puzzle is weak. What's your opinion?Why would one need to solve 20 puzzles? I can't figure the logic.Perhaps someone here can help me with this.Thank you very much for your time.Regards.

:)

Brink · Mar 16, 2024

New AI task suggestions in Microsoft To Do web application

Plan your day better with intelligent task suggestions.

A well-formed daily plan can do wonders to boost your productivity and help you end each day on a high note. The My Day list in To Do gives you a blank slate to plan your day.

We’re committed to making your daily planning experience better and have introduced intelligent task suggestions in My Day on To Do’s web application so you can focus on tasks that matter to you. We use AI to identify tasks that seem important, suggesting them based on keywords. These suggestions also include tasks that have deadlines and tasks you starred :star:.

Try the feature now!

Head to To Do web application and select the My Day list. We’ve added a new section, Tasks that seem important, in the suggestions pane :light_bulb:. It can help you identify tasks to add to your My Day list so you can focus on getting things done. If a suggestion isn’t relevant to you, just select more options > This isn't relevant to me.

We’ll show up to seven tasks we identify as most relevant to you in this section. It’ll update as you add new tasks or edit existing ones. Your urgent tasks, like ones due today or tomorrow or the ones that are overdue, will show up here. All other tasks with due dates will continue to show up in the Later and Earlier sections of the suggestions pane.

The feature is currently available on the To Do web application and only for To Do in English.

Note: Tasks assigned to you in Microsoft Planner show up in To Do’s Assigned to you list, but these tasks currently aren’t suggested in the Tasks that seem important section.

We hope that AI-powered task suggestions help you stay focused on your key tasks. We’d love to hear your feedback. Let us know in the comments below or over on Twitter and Facebook. You can also write to us at L: todofeedback@microsoft.com.
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Source: https://techcommunity.microsoft.com/...o/ba-p/2052607

Brink · Mar 16, 2024

Microsoft Announces AI Customer Commitments

AI is creating unparalleled opportunities for businesses of every size and across every industry. We are seeing our customers embrace AI services to drive innovation, increase productivity and solve critical problems for humanity, such as the development of breakthrough medical cures and new ways to meet the challenges of climate change. At the same time, there are legitimate concerns about the power of the technology and the potential for it to be used to cause harm rather than benefits. It’s not surprising, in this context, that governments around the world are looking at how existing laws and regulations can be applied to AI and are considering what new legal frameworks may be needed. Ensuring the right guardrails for the responsible use of AI will not be limited to technology companies and governments: every organization that creates or uses AI systems will need to develop and implement its own governance systems. That’s why today we are announcing three AI Customer Commitments to assist our customers on their responsible AI journey.

First, we will share what we are learning about developing and deploying AI responsibly and assist you in learning how to do the same. Microsoft has been on a responsible AI journey since 2017, harnessing the skills of nearly 350 engineers, lawyers and policy experts dedicated to implementing a robust governance process that guides the design, development and deployment of AI in safe, secure and transparent ways. More specifically we are:

Sharing expertise: We are committed to sharing this knowledge and expertise with you by publishing the key documents we developed during this process so that you can learn from our experiences. These include our Responsible AI Standard, AI Impact Assessment Template, AI Impact Assessment Guide, Transparency Notes, and detailed primers on the implementation of our responsible AI by design approach.

Providing training curriculum: We will also share the work we are doing to build a practice and culture of responsible AI at Microsoft, including key parts of the curriculum that we use to train Microsoft employees.

Creating dedicated resources: We will invest in dedicated resources and expertise in regions around the world to respond to your questions about deploying and using AI responsibly.

Second, we are creating an AI Assurance Program to help you ensure that the AI applications you deploy on our platforms meet the legal and regulatory requirements for responsible AI. This program will include the following elements:

Regulator engagement support: We have extensive experience helping customers in the public sector and highly regulated industries manage the spectrum of regulatory issues that arise when dealing with the use of information technology. For example, in the global financial services industry, we worked closely for a number of years with both customers and regulators to ensure that this industry could pursue digital transformation on the cloud while complying with its regulatory obligations. One learning from this experience has been the industry’s requirement that financial institutions verify customer identities, establish risk profiles and monitor transactions to help detect suspicious activity, the “know your customer” requirements. We believe that this approach can apply to AI in what we are calling “KY3C,” an approach that creates certain obligations to know one’s cloud, one’s customers and one’s content. We want to work with you to apply KY3C as part of our AI Assurance Program.

Risk framework implementation: We will attest to how we are implementing the AI Risk Management Framework recently published by the U.S. National Institute of Standards and Technology (NIST) and will share our experience engaging with NIST’s important ongoing work in this area.

Customer councils: We will bring customers together in customer councils to hear their views on how we can deliver the most relevant and compliant AI technology and tools.

Regulatory advocacy: Finally, we’ll play an active role in engaging with governments to promote effective and interoperable AI regulation. The recently launched Microsoft blueprint for AI governance presents our proposals to governments and other stakeholders for appropriate regulatory frameworks for AI. We have made available a presentation of this blueprint by Microsoft Vice Chair and President Brad Smith and a white paper discussing it in detail.

Third, we will support you as you implement your own AI systems responsibly, and we will develop responsible AI programs for our partner ecosystem.

Dedicated resources: We will create a dedicated team of AI legal and regulatory experts in regions around the world as a resource for you to support your implementation of responsible AI governance systems in your businesses.

Partner support: Many of our partners have already created comprehensive practices to help customers evaluate, test, adopt and commercialize AI solutions, including creating their own responsible AI systems. We are launching a program with selected partners to leverage this expertise to assist our mutual customers in deploying their own responsible AI systems. Today we can announce that PwC and EY are our launch partners for this exciting program.

Ultimately, we know that these commitments are only the start, and we will have to build on them as both the technology and regulatory conditions evolve. But we are also excited by this opportunity to partner more closely with our customers as we continue on the responsible AI journey together.
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Source: https://blogs.microsoft.com/blog/202...r-commitments/

Brink · Mar 16, 2024

Microsoft’s framework for building AI systems responsibly

Today we are sharing publicly Microsoft’s Responsible AI Standard, a framework to guide how we build AI systems. It is an important step in our journey to develop better, more trustworthy AI. We are releasing our latest Responsible AI Standard to share what we have learned, invite feedback from others, and contribute to the discussion about building better norms and practices around AI. Guiding product development towards more responsible outcomes AI systems are the product of many different decisions made by those who develop and deploy them. From system purpose to how people interact with AI systems, we need to proactively guide these decisions toward more beneficial and equitable outcomes. That means keeping people and their goals at the center of system design decisions and respecting enduring values like fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. The Responsible AI Standard sets out our best thinking on how we will build AI systems to uphold these values and earn society’s trust. It provides specific, actionable guidance for our teams that goes beyond the high-level principles that have dominated the AI landscape to date. The Standard details concrete goals or outcomes that teams developing AI systems must strive to secure. These goals help break down a broad principle like ‘accountability’ into its key enablers, such as impact assessments, data governance, and human oversight. Each goal is then composed of a set of requirements, which are steps that teams must take to ensure that AI systems meet the goals throughout the system lifecycle. Finally, the Standard maps available tools and practices to specific requirements so that Microsoft’s teams implementing it have resources to help them succeed.

The core components of Microsoft’s Responsible AI Standard The need for this type of practical guidance is growing. AI is becoming more and more a part of our lives, and yet, our laws are lagging behind. They have not caught up with AI’s unique risks or society’s needs. While we see signs that government action on AI is expanding, we also recognize our responsibility to act. We believe that we need to work towards ensuring AI systems are responsible by design. Refining our policy and learning from our product experiences Over the course of a year, a multidisciplinary group of researchers, engineers, and policy experts crafted the second version of our Responsible AI Standard. It builds on our previous responsible AI efforts, including the first version of the Standard that launched internally in the fall of 2019, as well as the latest research and some important lessons learned from our own product experiences. Fairness in Speech-to-Text Technology The potential of AI systems to exacerbate societal biases and inequities is one of the most widely recognized harms associated with these systems. In March 2020, an academic study revealed that speech-to-text technology across the tech sector produced error rates for members of some Black and African American communities that were nearly double those for white users. We stepped back, considered the study’s findings, and learned that our pre-release testing had not accounted satisfactorily for the rich diversity of speech across people with different backgrounds and from different regions. After the study was published, we engaged an expert sociolinguist to help us better understand this diversity and sought to expand our data collection efforts to narrow the performance gap in our speech-to-text technology. In the process, we found that we needed to grapple with challenging questions about how best to collect data from communities in a way that engages them appropriately and respectfully. We also learned the value of bringing experts into the process early, including to better understand factors that might account for variations in system performance. The Responsible AI Standard records the pattern we followed to improve our speech-to-text technology. As we continue to roll out the Standard across the company, we expect the Fairness Goals and Requirements identified in it will help us get ahead of potential fairness harms. Appropriate Use Controls for Custom Neural Voice and Facial Recognition Azure AI’s Custom Neural Voice is another innovative Microsoft speech technology that enables the creation of a synthetic voice that sounds nearly identical to the original source. AT&T has brought this technology to life with an award-winning in-store Bugs Bunny experience, and Progressive has brought Flo’s voice to online customer interactions, among uses by many other customers. This technology has exciting potential in education, accessibility, and entertainment, and yet it is also easy to imagine how it could be used to inappropriately impersonate speakers and deceive listeners. Our review of this technology through our Responsible AI program, including the Sensitive Uses review process required by the Responsible AI Standard, led us to adopt a layered control framework: we restricted customer access to the service, ensured acceptable use cases were proactively defined and communicated through a Transparency Note and Code of Conduct, and established technical guardrails to help ensure the active participation of the speaker when creating a synthetic voice. Through these and other controls, we helped protect against misuse, while maintaining beneficial uses of the technology. Building upon what we learned from Custom Neural Voice, we will apply similar controls to our facial recognition services. After a transition period for existing customers, we are limiting access to these services to managed customers and partners, narrowing the use cases to pre-defined acceptable ones, and leveraging technical controls engineered into the services. Fit for Purpose and Azure Face Capabilities Finally, we recognize that for AI systems to be trustworthy, they need to be appropriate solutions to the problems they are designed to solve. As part of our work to align our Azure Face service to the requirements of the Responsible AI Standard, we are also retiring capabilities that infer emotional states and identity attributes such as gender, age, smile, facial hair, hair, and makeup. Taking emotional states as an example, we have decided we will not provide open-ended API access to technology that can scan people’s faces and purport to infer their emotional states based on their facial expressions or movements. Experts inside and outside the company have highlighted the lack of scientific consensus on the definition of “emotions,” the challenges in how inferences generalize across use cases, regions, and demographics, and the heightened privacy concerns around this type of capability. We also decided that we need to carefully analyze all AI systems that purport to infer people’s emotional states, whether the systems use facial analysis or any other AI technology. The Fit for Purpose Goal and Requirements in the Responsible AI Standard now help us to make system-specific validity assessments upfront, and our Sensitive Uses process helps us provide nuanced guidance for high-impact use cases, grounded in science. These real-world challenges informed the development of Microsoft’s Responsible AI Standard and demonstrate its impact on the way we design, develop, and deploy AI systems. For those wanting to dig into our approach further, we have also made available some key resources that support the Responsible AI Standard: our Impact Assessment template and guide, and a collection of Transparency Notes. Impact Assessments have proven valuable at Microsoft to ensure teams explore the impact of their AI system – including its stakeholders, intended benefits, and potential harms – in depth at the earliest design stages. Transparency Notes are a new form of documentation in which we disclose to our customers the capabilities and limitations of our core building block technologies, so they have the knowledge necessary to make responsible deployment choices.

The Responsible AI Standard is grounded in our core principles A multidisciplinary, iterative journey Our updated Responsible AI Standard reflects hundreds of inputs across Microsoft technologies, professions, and geographies. It is a significant step forward for our practice of responsible AI because it is much more actionable and concrete: it sets out practical approaches for identifying, measuring, and mitigating harms ahead of time, and requires teams to adopt controls to secure beneficial uses and guard against misuse. You can learn more about the development of the Standard in this . While our Standard is an important step in Microsoft’s responsible AI journey, it is just one step. As we make progress with implementation, we expect to encounter challenges that require us to pause, reflect, and adjust. Our Standard will remain a living document, evolving to address new research, technologies, laws, and learnings from within and outside the company. There is a rich and active global dialog about how to create principled and actionable norms to ensure organizations develop and deploy AI responsibly. We have benefited from this discussion and will continue to contribute to it. We believe that industry, academia, civil society, and government need to collaborate to advance the state-of-the-art and learn from one another. Together, we need to answer open research questions, close measurement gaps, and design new practices, patterns, resources, and tools. Better, more equitable futures will require new guardrails for AI. Microsoft’s Responsible AI Standard is one contribution toward this goal, and we are engaging in the hard and necessary implementation work across the company. We’re committed to being open, honest, and transparent in our efforts to make meaningful progress.
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Source: https://blogs.microsoft.com/on-the-i...s-responsibly/

Windows 10: Is AI helpful to Microsoft or harmful?

Is AI helpful to Microsoft or harmful?

Is AI helpful to Microsoft or harmful?

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