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FINRA Reminds Members of Regulatory Obligations When Using Generative Artificial Intelligence (AI) and Large Language Models

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On June 27, 2024, the Financial Industry Regulatory Authority, Inc. (“FINRA”) released Regulatory Notice 24-09 (the “Notice”), reminding member firms that the application of artificial intelligence (“AI”), including large language models (“LLMs”) and other generative AI (“Gen AI”) technologies, must adhere to existing FINRA rules and securities laws, similar to any other technology used by firms.
The Notice clarifies that it does not introduce new legal or regulatory requirements nor alter interpretations of existing obligations under federal securities laws.
FINRA’s heightened scrutiny of AI stems from its recognition of AI as an emerging risk, as outlined in its 2024 Annual Regulatory Oversight Report. Similarly, the U.S. Securities and Exchange Commission (“SEC”) has proposed rules on predictive data analytics, reflecting growing regulatory attention on AI use among broker-dealers and investment advisers.
In addition, there has been enforcement focus on AI technologies within broker-dealer operations, reflecting ongoing regulatory concerns and industry challenges.
As member firms integrate Gen AI or similar technologies into their operations, FINRA underscores the importance of understanding the implications and ensuring compliance with regulatory obligations.
Background
While the use of AI by member firms is not new, recent advancements, particularly in Gen AI, have expanded capabilities to generate text, synthetic data, images, and other media in response to prompts. LLMs, a type of Gen AI, utilize deep learning techniques and extensive language datasets to identify, summarize, predict, and create new textual content. Despite promising potential applications for investors and firms alike, Gen AI raises concerns about accuracy, privacy, bias, intellectual property, and vulnerabilities to malicious exploitation.
Regulatory Obligations When Using Gen AI Technology
FINRA emphasizes its rules are technologically neutral and adapt dynamically to technological advancements in member firms’ operations. These rules apply uniformly when firms use AI technologies, regardless of whether the technology is developed in-house or obtained from third-party sources, including embedded features in existing products.
For instance, FINRA Rule 3110 (Supervision) mandates member firms to maintain a supervisory system tailored to their business needs. Firms using Gen AI for supervision, such as monitoring electronic communications, must establish policies covering technology governance, including model risk management, data privacy, data integrity, and AI model reliability and accuracy.
Firms are urged to conduct thorough evaluations of Gen AI tools before deployment to ensure continued compliance with FINRA rules. Depending on the specific use case, the application of Gen AI could impact nearly all aspects of a firm’s regulatory responsibilities.
Further Considerations
FINRA encourages member firms encountering ambiguous applications of FINRA rules related to AI to seek interpretive guidance from its staff. Moreover, ongoing dialogue with Risk Monitoring Analysts is recommended to address AI-related issues or other business changes.
Looking ahead, FINRA remains open to providing additional guidance or proposing rule amendments as necessary to address the evolving landscape of AI technology in the financial industry.
Source: mayerbrown.com
The post FINRA Reminds Members of Regulatory Obligations When Using Generative Artificial Intelligence (AI) and Large Language Models appeared first on HIPTHER Alerts.

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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
The post Brazil authority suspends Meta’s AI privacy policy, seeks adjustment appeared first on HIPTHER Alerts.

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