This special session is organised and supported by Liverpool Hope University, United Kingdom.
- Dr. Emad Tariq, Liverpool Hope University UK;
- Dr. Neil Buckley, Liverpool Hope University
The world has moved to a digital era and AI becomes the core of many businesses. AI is crafting an integrated technology with humans in order to create synthetic intelligence by gathering data about who we are, what we do and how we think to work together. The scale of AI is much more efficient in dealing with the massive amount of data on daily basis such as crime, immigration, health, environment, education, traffic and financial stock markets. Today, AI is gathering and monitoring data of approximately 2.5 ZB per day and which beyond human capacity. Large amount of diverse ad accurate data is required to develop AI algorithms and enhance the recognition capabilities of machine learning applications.
Networks and computers are absolutely everywhere, however, AI doesn’t cover each area yet. AI has major challenges that need potential solutions to meter and monitor the world, as well as building smarter future. Situational awareness remains a core challenge of AI recognition process during transactions or dynamic decision making applications. In addition, people very concerned about the human rights, data protection and data control when gathering this massive amount of data and which creates a serious challenge. For example, Social media platforms are using AI algorithms to predict users’ behaviors and influence them, however, users are unaware about the responsible people who control date and write AI algorithms to make decisions. Furthermore, data collection process always subjected to bias, while AI algorithms completely depend on quality of data to ensure taking accurate decisions. What if data are missing or inaccurate and which lead to wrong algorithms that biased the decision making process?
Likewise, privacy consent and data transparency do face another challenge such as collecting data from children and teenagers, as well as data ownership can be easily breached by reselling it to another countries or companies. Moreover, cyber-attacks remain as a vital challenge to AI, for instance, sophisticated attacks can control and manipulate AI systems and which affects the accuracy of AI algorithms, analysis and the results. AI depends on the network and cybercriminals can incur damage of data or information overload and operational network failure, consequently it affects the efficiency of online data collection.
Aforementioned, there is an urgent need for dynamic data-driven application systems to adapt accurate measurements and resources in accordance with fast changing situations. AI experts, professional tutors and academics are required to provide validity and reliability of data collection in order to avoid bias and discrimination within the decision-making process. AI systems need to increase the ethical accountability, as well as to reduce risks of technical and legal aspects. AI needs optimisation with cybersecurity to ensure safety and privacy of data.
Therefore, this special session invites authors to participate in finding potential solutions. The session invites academics and professional tutors to submit high research papers, covering topics which include (but are not limited to) the following:
- AI perception, situational awareness and decision-making.
- Data privacy, protection, ownership, and control in AI.
- AI and ethical accountability.
- Cyber-attacks in AI systems and Sensors: Threats and Solutions. Cybersecurity in market research and data collection platforms.
- Cybersecurity in Augmented Intelligence Process.
- Bias/discrimination in market research, data collection and analysis at AI systems.
- Customer awareness and solutions in AI: B2C, B2B, B2G perspectives.
|Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.|