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Balancing innovation & security within the Wild West of shadow AI

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In just eighteen months, Generation AI (Gen AI) has revolutionized business operations, driving unprecedented levels of efficiency and productivity. However, this rapid innovation has also introduced a new challenge: Shadow AI, defined as the unauthorized use of AI applications within organizations, often without the oversight or knowledge of IT and security teams.
Shadow AI resembles the Wild West of the tech world—a frontier where sensitive data may be shared recklessly, and the consequences of Gen AI misuse are unpredictable. Employees unknowingly risk exposing confidential information while using Gen AI tools for tasks like drafting emails, content creation, or data analysis. This lack of visibility and control over Gen AI usage can lead to data breaches, compliance issues, and damage to the organization’s reputation.
Addressing the challenges posed by Shadow AI requires a proactive and methodical approach while harnessing the innovation and productivity benefits of Gen AI:
Step One: Discovery Organizations need to gain visibility into the AI applications being utilized internally. By employing methods such as Single Sign-On (SSO) integration, Identity and Access Management (IAM) tools, and browser agent monitoring, IT and security teams can identify unauthorized AI applications and evaluate associated risks.
Step Two: Intelligence Gathering It’s essential to gather intelligence on these applications—understanding who has access, what data is shared, and how frequently these tools are used. Armed with this information, organizations can categorize AI applications based on risk and establish clear policies and guidelines for their appropriate use.
Step Three: Control Implementing robust processes to enforce policies and restrict access to unauthorized AI applications is crucial. This can be achieved through user education, policy enforcement measures, and technical controls such as access management, regular access reviews, and data protection solutions. Establishing a cycle of response, review, and reinforcement helps organizations effectively manage the risks associated with Shadow AI.
The landscape of AI is dynamic and requires tailored approaches rather than one-size-fits-all solutions. Collaboration between IT, security, and business teams is essential to strike a balance between security and productivity. Regular communication, training initiatives, and awareness programs empower employees to understand the risks associated with AI usage and make informed decisions.
As we continue to explore the possibilities of AI, it’s imperative to recognize both the significant risks and the immense opportunities it presents. By proactively addressing the challenges of Shadow AI, organizations can leverage AI’s power while safeguarding their data and systems from potential harm.
Source: bdtechtalks.com

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Bytes Of Healing: Digital Innovation Meets Patient-Centric Care Through AI/ML

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In the rapidly evolving healthcare landscape, digital innovation driven by Artificial Intelligence (AI) and Machine Learning (ML) is transforming patient care, ushering in a new era of personalized and effective treatment strategies.
Leading this charge is Swapna Nadakuditi, a seasoned expert renowned for her pioneering work at the intersection of data analytics and healthcare.
Swapna Nadakuditi has achieved significant milestones in her career, particularly through her leadership in the Bytes of Healing initiative. Over the past five years, her contributions have been crucial in leveraging AI/ML technologies to enhance patient-centric care. She specializes in utilizing extensive datasets—from medical records to demographic information—to develop predictive models that identify individuals at heightened health risks, such as COPD, diabetes, and CKD. This data-driven approach not only facilitates early disease detection but also enables tailored healthcare solutions that improve patient outcomes.
One of Swapna’s major achievements includes successfully implementing Natural Language Processing (NLP) techniques to extract diagnosis codes from unstructured medical records. This innovation has streamlined clinical documentation processes and enhanced the accuracy of predictive analytics, optimizing healthcare delivery.
In addition to her technical accomplishments, Swapna Nadakuditi has navigated significant challenges inherent in AI/ML integration within healthcare. These challenges include ensuring data privacy compliance, scaling AI solutions using distributed computing frameworks, and fostering interdisciplinary collaboration across data science and healthcare domains. Her proactive approach to overcoming these obstacles underscores her commitment to advancing healthcare through technological innovation.
Swapna’s work has yielded measurable outcomes, including improved risk scoring accuracy, leading to enhanced revenue from risk adjustment and minimized coding errors in healthcare billing. Furthermore, her initiatives have bolstered patient engagement and satisfaction through personalized interventions, augmenting membership growth and service efficiency.
Looking ahead, Swapna Nadakuditi advocates for continued innovation in healthcare, emphasizing the transformative potential of AI technologies integrated with wearable devices and IoT. She predicts that advancements in AI, coupled with regulatory support, will reshape healthcare delivery by making it more efficient, predictive, and patient-centered.
Swapna Nadakuditi’s leadership in Bytes of Healing exemplifies how AI and ML are reshaping healthcare, turning precision medicine and patient-centric care from distant goals into tangible realities. Her pioneering efforts highlight the transformative potential of technology in improving health outcomes and setting new benchmarks for the industry. As she continues to innovate at the intersection of data science and healthcare, Swapna’s vision for the future includes further integration of AI with wearable devices and IoT, promising even more personalized and effective healthcare solutions.
Source: freepressjournal.in
The post Bytes Of Healing: Digital Innovation Meets Patient-Centric Care Through AI/ML appeared first on HIPTHER Alerts.

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LAUSD and AllHere: 4 Takeaways Amid New Doubts About the Far-Reaching AI Project

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One of the most ambitious experiments in integrating artificial intelligence into public schools is making headlines as the tech company behind it, AllHere, faces uncertainty.
Education companies and school district leaders working on similar AI projects need to pay attention.
Background on AllHere and LAUSD
AllHere has been collaborating with the Los Angeles Unified School District (LAUSD) to embed an AI tool designed to assist families with academic and logistical questions. However, the company recently furloughed most of its staff and changed leadership, raising concerns about the project’s future.
While the company has remained silent since announcing the furloughs on its website, LAUSD officials have stated that the school system owns the AI tool and will be involved in any potential acquisition of AllHere.
Data Privacy Concerns
Questions have also arisen about the data privacy practices of AllHere’s AI-powered chatbot. A former employee alleged that the platform was collecting data in violation of LAUSD’s policies on sharing students’ personally identifiable information and best data-protection practices.
Broader Implications for AI in Education
The situation with AllHere highlights broader concerns for AI-focused education companies regarding their readiness to meet school districts’ complex needs, particularly on a large scale like LAUSD.
Key Takeaways for AI-Education Partnerships

Clear Goals from the Outset:

LAUSD’s project had broad and ambitious goals, aimed at addressing chronic absenteeism using advanced analytics and AI chatbot features.
The district’s request for proposals (RFP) called for a fully integrated portal system to provide a “one-stop” access point for students, teachers, families, and administrators.

Meeting District Demands vs. Attracting Venture Capital:

Education companies have attracted significant venture capital, with AI-focused projects receiving substantial investment.
AllHere, launched in 2016 with backing from the Harvard Innovation Lab, raised over $12 million and secured a $6 million contract with LAUSD.
However, venture capital does not guarantee readiness to meet the complexities of delivering data-secure AI solutions. Ensuring compliance and data security is crucial.

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Complexities of Data Security:

Providing AI solutions to school districts involves navigating complex data privacy and security requirements.
Ensuring that AI tools comply with district policies and best practices is essential to protect student data.

Collaboration and Transparency:

Successful AI integration in education requires clear communication and collaboration between tech companies and school districts.
Transparency in data handling and adherence to privacy standards are critical to maintaining trust and ensuring the long-term success of AI projects in schools.

Source: marketbrief.edweek.org
The post LAUSD and AllHere: 4 Takeaways Amid New Doubts About the Far-Reaching AI Project appeared first on HIPTHER Alerts.

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Brazil authority suspends Meta’s AI privacy policy, seeks adjustment

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Brazil’s National Data Protection Authority (ANPD) has immediately suspended the validity of Meta’s new privacy policy, which involves the use of personal data for training generative artificial intelligence systems.
The ANPD’s preventive measure, published in Brazil’s official gazette, halts the processing of personal data across all Meta products, including data from individuals who do not use the tech giant’s platforms. The authority, under the Justice Ministry, has imposed a daily fine of 50,000 reais ($8,836.58) for non-compliance.
The decision was based on the “imminent risk of serious and irreparable or difficult-to-repair damage to the fundamental rights of affected holders.”
Meta is required to amend its privacy policy to remove the section related to using personal data for AI training. Additionally, the company must issue an official statement confirming the suspension of personal data processing for that purpose.
In response, Meta expressed disappointment with ANPD’s decision, calling it a “setback for innovation” that will delay the benefits of AI for Brazilians. The company stated, “We are more transparent than many players in this industry who have used public content to train their models and products. Our approach complies with privacy laws and regulations in Brazil.”
Source: thehindu.com
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