Assistant Lecturer Russul Mushtaq Talib from the Department of Community Health Technologies at Al-Mustaqbal University prepared a scientific article entitled “Applications of Artificial Intelligence in Life Sciences and Modern Medicine: Assessing the Balance Between Technological Revolution and Community Health and Environmental Risks.” The article examines the ongoing debate surrounding the integration of artificial intelligence technologies into the life sciences and biomedical fields, as well as their multidimensional impacts, with a particular focus on achieving a balance between their technological and economic benefits and the associated community health and environmental risks. The article reviewed the potential benefits of artificial intelligence in the life sciences and modern medicine, particularly accelerating drug discovery, advancing precision and personalized medicine, addressing challenges in computational biology, and developing brain-computer interface technologies. At the same time, it addressed a range of challenges associated with algorithmic bias, genetic data privacy, limited explainability in medical decision-making, and unintended impacts on the biological environment. The article noted that the massive expansion of biological and genetic data has driven a global transition from traditional laboratory-based observational approaches toward big data-driven methodologies. It highlighted that artificial intelligence provides innovative solutions for diagnosing complex diseases and designing personalized therapies; however, this transformation raises a number of concerns related to biosafety, the ethics of implementation, and its direct and indirect long-term effects on public health and human ecosystems. From a technological and economic perspective, the article examined the role of artificial intelligence in addressing challenges in computational and synthetic biology through highly accurate prediction of three-dimensional protein structures, as demonstrated by models such as AlphaFold. Such advances open new avenues for designing environmental enzymes and engineered proteins for the treatment of diseases. The article also highlighted the importance of artificial intelligence in advancing precision and personalized medicine through genomic sequencing analysis and Multi-Omics approaches, contributing to the development of individualized treatment plans, improving therapeutic response, and determining the most appropriate treatment for each patient. Furthermore, the article demonstrated the potential of artificial intelligence to reduce the costs and challenges associated with drug development by shortening the drug development process from decades to only a few months through digital chemical screening and the prediction of compound efficacy. This can reduce production costs and positively impact healthcare costs. The article also addressed brain-computer interface (BCI) technologies and their role in decoding electrical signals from the brain and restoring motor and sensory functions in individuals with paralysis through intelligent prosthetic limbs. On the other hand, the article discussed the major community health, ethical, and environmental risks, including algorithmic bias resulting from reliance on demographically unbalanced datasets, which may lead to inaccurate diagnostic outcomes for certain racial and ethnic groups. It also highlighted the risks associated with violations of genetic data privacy, including the leakage or exploitation of patients’ medical records and genetic information by commercial entities. The article further highlighted the issue of explainability and transparency, particularly the so-called “black box” phenomenon in AI-derived medical decisions, which may make it difficult for healthcare professionals to understand the precise factors underlying algorithmic diagnoses. It also addressed unintended effects on the biological environment, including the possibility of unexpected genetic mutations resulting from the use of artificial intelligence in the modification of microorganisms or crops, which could potentially threaten biodiversity. The article emphasized the importance of the technological role of Community Health Technology specialists in addressing these challenges through pre-adoption algorithmic evaluation, including subjecting medical models and genetic prediction tests to accuracy and biosafety assessments in accordance with World Health Organization (WHO) protocols. It also stressed the importance of strengthening ethical tracking and transparency systems, ensuring patients’ right to information and informed consent, and encrypting biological data to prevent unauthorized access or exploitation. The article further emphasized the importance of conducting longitudinal epidemiological studies to monitor and follow up on any health-related and behavioral changes or deviations within communities that adopt AI-managed healthcare systems. The article concluded that integrating artificial intelligence into the life sciences and modern medicine represents a powerful technological tool for advancing global healthcare; however, it is not without risks. Therefore, achieving a careful balance between scientific innovation and the Precautionary Principle is essential, alongside strengthening regulatory frameworks and technological oversight to ensure that this digital transformation serves community health without compromising biosafety. The article drew upon a number of suggested scientific references, including Nature Medicine (2024) on the applications and governance of artificial intelligence in biomedicine and public health, publications by the World Health Organization (WHO) concerning the ethics and governance of artificial intelligence for health, and the Journal of Computational Biology on AI-driven multi-omics integration in precision medicine. Al-Mustaqbal University – The First University in Iraq