Ethical aspects and future of artificial intelligence

Kumar, Narendra; Kharkwal, Nidhi; Kohli, Rashi; Choudhary, Shakeeluddin

doi:10.1109/iciccs.2016.7542339

Cited by 36 publications

(17 citation statements)

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“…"We have to think what the moral issues are and how we can use Artificial Intelligence to make a better decision for both the people and society" [8]. Human beings use emotions in consideration of making decisions, this is at present missing from AI.…”

Section: Ai Security Regulations and Ethicsmentioning

confidence: 99%

“…Currently there is rapid development of AI in the military which brings the need for not just security but also regulations, this also highlights the risk of autonomous AI making decisions on aspects of warfare without standard regulations or security. "Ethical decisions are being faced to support or oppose autonomous weapons systems" [8]. "It would be a security threat if AI with self-aware ability could not be fully controlled by humans" [2].…”

Section: Ai Security Regulations and Ethicsmentioning

confidence: 99%

“…"It would be a security threat if AI with self-aware ability could not be fully controlled by humans" [2]. "Ethics is a concern with the moral behaviour of the machine which is designed and used for many purposes" [8]. AI is advancing rapidly but ethics and security are not, AI is involved with DNA mapping, what security, regulations and ethics are developers following?…”

Section: Ai Security Regulations and Ethicsmentioning

confidence: 99%

See 2 more Smart Citations

The intrinsically linked future for human and Artificial Intelligence interaction

Miller

2019

J Big Data

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Human and artificial intelligence interaction are presenting prodigious and exciting technological opportunities for mutual development even in today's current technological climate, but the real potential for mutual development is in the foreseeable future and beyond which has the potential to be mind-boggling. With the continued rapid development of not just technology but also in quantum research the potential for Artificial Intelligence to evolve at a frightening speed is within our grasp. The building blocks to achieve this phenomenal leap in technology consists of Quantum Computing, Big Data and brain computer interface (BCI), each becoming stepping stones and advancing to such a stage where once technology only thought of in science fiction will be an everyday feature of modern human and AI technology. AI and human beings bring their own unique traits with each learning from the other, humans bring attributes including experience, values and judgement which can weave together with the enormous attributes

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Section: Ai Security Regulations and Ethicsmentioning

confidence: 99%

Section: Ai Security Regulations and Ethicsmentioning

confidence: 99%

Section: Ai Security Regulations and Ethicsmentioning

confidence: 99%

See 1 more Smart Citation

The intrinsically linked future for human and Artificial Intelligence interaction

Miller

2019

J Big Data

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“…7. Legal Aspects: The IoT system has many integrated services provided by multiple partners, collaborative ventures, and new business models will give rise to legal challenges and legal relationships will need to be addressed between the parties as will liability, IP, privacy, security, insurance and other regulatory issues [33].…”

Section: Accuracy and Speedmentioning

confidence: 99%

Intelligence of Things: Opportunities & Challenges

Atlam

Walters

Wills

2018

2018 3rd Cloudification of the Internet of Things (CIoT)

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The Internet of Things (IoT) is a promising technology that can connect and communicate virtual and physical objects globally. It allows billions of devices to be connected and communicate with each other to share information that creates new application and services. These services result in improving our quality of life. On the other hand, Artificial Intelligence (AI) is applied in many fields of science. It aims to understand techniques that require an intelligent action and solve complex problems. Integrating IoT with AI will create a powerful technology that can solve many of IoT problems that relate to the huge amount of data created by different IoT devices. With the huge analytic capabilities of AI, IoT data can be analysed efficiently to extract meaningful information. In addition, AI can help IoT devices to interact with humans and other objects intelligently and make autonomous decisions. This paper provides an overview of the integration of the IoT with AI by highlighting the integration benefits and opportunities of AI in different IoT applications. Challenges standing in the way of successful convergence of IoT with AI are also discussed. We can conclude that the integration of AI with IoT will generate a robust technology that can help companies to avoid unplanned downtime, increase operating efficiency, and enable new IoT applications and services.

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“…In sensitive areas such as airports [1] and electronic warfare-type battlefield [2], anti-jamming techniques are needed for against illegal jammers. With the development of artificial intelligence (AI) [3], communication devices are becoming increasingly intelligent [4]. Users are able to learn the jamming modes with the help of AI technologies, the probability of being jammed can be reduced by making the right decision, such as switching to idle communication frequencies [5] or adjusting the communication power [6].…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Deep Reinforcement Learning-Based Anti-Jamming Method Confronting Intelligent Jammer

Wang

Liu

et al. 2019

Applied Sciences

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With the development of access technologies and artificial intelligence, a deep reinforcement learning (DRL) algorithm is proposed into channel accessing and anti-jamming. Assuming the jamming modes are sweeping, comb, dynamic and statistic, the DRL-based method through training can almost perfectly avoid jamming signal and communicate successfully. Instead, in this paper, from the perspective of jammers, we investigate the performance of a DRL-based anti-jamming method. First of all, we design an intelligent jamming method based on reinforcement learning to combat the DRL-based user. Then, we theoretically analyze the condition when the DRL-based anti-jamming algorithm cannot converge, and provide the proof. Finally, in order to investigate the performance of DRL-based method, various scenarios where users with different communicating modes combat jammers with different jamming modes are compared. As the simulation results show, the theoretical analysis is verified, and the proposed RL-based jamming can effectively restrict the performance of DRL-based anti-jamming method.

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Ethical aspects and future of artificial intelligence

Cited by 36 publications

References 0 publications

The intrinsically linked future for human and Artificial Intelligence interaction

The intrinsically linked future for human and Artificial Intelligence interaction

Intelligence of Things: Opportunities & Challenges

On the Performance of Deep Reinforcement Learning-Based Anti-Jamming Method Confronting Intelligent Jammer

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