AI-Powered Employee Experience

Advances in human resources management and organizational development book series, Journal Year: 2023, Volume and Issue: unknown, P. 166 - 181

Published: Dec. 29, 2023

AI has become an indispensable tool for businesses seeking to enhance the employee experience. Businesses that implement it can increase satisfaction, customer service, and decrease cost per served – ultimately adding significant business value. Artificial intelligence instruments improve experiences across several areas: recruitment, onboarding, training, performance management. Furthermore, this use case will profoundly impact overall.

Language: Английский

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Guardians of the Algorithm

Advances in computational intelligence and robotics book series, Journal Year: 2024, Volume and Issue: unknown, P. 196 - 210

Published: March 4, 2024

The emergence of artificial intelligence (AI) and data enquiry priciples uncovered immese technological possibilities, but it has also presented a range ethical concerns that require careful supervision moderation to avoid unintended consequences. This chapter is thorough examination emphasizes the crucial importance human intervention in upholding integrity AI systems data-driven processes. It not only as regulatory structure, an essential element development execution systems. study examines many approaches oversight, including both direct advanced monitoring techniques, can be incorporated at every stage lifecycle, from original creation post-deployment. showcases case studies real-world situations illustrate instances when lack resulted violations, conversely, where its presence effectively reduced dangers.

Language: Английский

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Mental Health in Messages

Advances in psychology, mental health, and behavioral studies (APMHBS) book series, Journal Year: 2024, Volume and Issue: unknown, P. 187 - 208

Published: Feb. 26, 2024

In an era dominated by digital communication, textual data offers a treasure of insights into human behaviour and emotions. today's digitally-driven world, the vast expanse generated from online interactions serves as profound indicator emotions behavioural nuances. This research delves deep realm sentiment analysis to uncover patterns indicative mental health states. Through robust examination synthetic datasets, study employs advanced techniques achieve same. These methods include analysis, topic modelling, pattern recognition, emotion detection. By interpreting these footprints, this underscores potential tool not just for understanding, but also predicting addressing challenges in communication mediums. The findings reveal that signs can be effective indicators conditions.

Language: Английский

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Unmasking the Shadows

Advances in human resources management and organizational development book series, Journal Year: 2024, Volume and Issue: unknown, P. 185 - 200

Published: Jan. 26, 2024

In the rapidly evolving landscape of artificial intelligence (AI), ethical ramifications its implementation have become a pressing concern. This chapter delves into darker facets AI deployment, examining cases where technology has been used in ways that defy established norms. It identifies common patterns and motivations behind unethical applications through comprehensive review real-world instances. Additionally, research underscores potential societal consequences these actions, emphasizing importance transparency, accountability, frameworks development deployment. serves as clarion call for community to prioritize ethics every application phase, ensuring is harnessed greater good rather than misused shadows.

Language: Английский

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Intelligent Conservation

Advances in systems analysis, software engineering, and high performance computing book series, Journal Year: 2024, Volume and Issue: unknown, P. 215 - 226

Published: March 29, 2024

Artificial Intelligence (AI) emerges as a potent ally in augmenting environmental monitoring and fortifying conservation efforts. Now we have seen escalating challenges the need for sustainable practices. This paper outlines innovative applications transformative potential of AI managing complexities ecological preservation monitoring. facilitates real-time processing interpretation voluminous data. It helps informed decision-making strategic planning initiatives. The employment AI-driven models technologies such machine learning algorithms, computer vision sensor networks has proven instrumental biodiversity. plays pivotal role enabling precision by facilitating identification prioritization critical areas requiring immediate intervention. contributes to development smart adaptive systems capable autonomously tracking analysing disturbances human encroachments.

Language: Английский

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AI in Building Systems for Perpetual Monitoring and Control of ESG Practices

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 104 - 114

Published: Jan. 1, 2025

Language: Английский

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Sustainability in the Digital Age

Advances in logistics, operations, and management science book series, Journal Year: 2024, Volume and Issue: unknown, P. 89 - 132

Published: Jan. 19, 2024

This chapter explores the convergence of Industry 4.0 technologies and sustainable supply chain practices, presenting a comprehensive overview these digital advancements' transformative potential. The begins by defining intersection between sustainability 4.0, emphasizing pivotal role in fostering environmentally socially responsible chains. With clear objectives mind, exploration delves into impact key on practices. discussion spans utilization internet things (IoT) for real-time monitoring, big data analytics informed decision-making, integration robotics to enhance ethical manufacturing.

Language: Английский

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Personalization of Travel Experiences Through Data Analytics

Advances in marketing, customer relationship management, and e-services book series, Journal Year: 2024, Volume and Issue: unknown, P. 127 - 144

Published: May 3, 2024

Travel and tourism represent a multifaceted sector, with the customer's journey from departure to return encompassing myriad interactions. A deeper comprehension of these interactions allows for enhanced planning aimed at enriching experience. The integration advanced data analytics has significantly focus on customer needs within travel industry. In this specific study, is applied tailor experiences visitors an amusement park, using comprehensive dataset fictional park explore how variables such as age, group makeup, admission time, ride preferences, eating habits can enhance visitor findings offer valuable insights into behaviors, facilitating customization services. For instance, age-related informs imposition restrictions, while arrival times aid in refining operations managing crowds more effectively.

Language: Английский

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Advancing Cybersecurity

Advances in information security, privacy, and ethics book series, Journal Year: 2024, Volume and Issue: unknown, P. 12 - 25

Published: May 16, 2024

This chapter presents an innovative approach to cybersecurity by applying anomaly detection techniques network and system data. The study uses a comprehensive dataset from simulated environments analyze various attack scenarios evaluate classification algorithms. ensemble model achieve superior accuracy integrates feature importance analysis. findings show that the proposed framework not only identifies known types but also detects novel threats, underscoring its potential as pivotal tool in cybersecurity. research paves way for new era These reveal achieves high identifying exhibits robustness detecting thereby arsenal. advocates paradigm shift towards proactive threat identification, emphasizing critical role of fortifying defenses against ever-increasing sophistication cyber-attacks.

Language: Английский

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Predictive Analytics for Reducing University Dropout Rates

Advances in human and social aspects of technology book series, Journal Year: 2024, Volume and Issue: unknown, P. 186 - 202

Published: June 14, 2024

Higher education institutions face a problem with student turnover that has many aspects and affects both students universities in different ways. Using predictive analytics machine learning, this study shows new way to deal problem. The main goal is create predicting algorithms can predict which are most likely drop out, so colleges get involved their lives timely effective way. As part of method, the authors collect preprocess large dataset from university records. This includes information about academic success, socioeconomic background, participation campus activities, psychological health. uses advanced learning methods look at all these data points. It focuses on feature selection engineering find important factors dropout. Rigid validation used test how well model works, making sure it accurately reliably future.

Language: Английский

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