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management of electric power transmission by controlling power flows and thereby lessening transmission losses and enhancing efficiency (Tsolakis et al. 2022). For instance, in AI applications the angle of solar panels is continuously changed to get the most sunlight, while the wind turbines’ blades angles are also varied in real time for efficient energy harvesting and to reduce the strain on the system (Lund and Mathiesen 2009). Additionally, AI assists in solving the problem of renewable energy intermittency by means of energy storage, that is, by increasing or decreasing the levels of charging and discharging of energy storage systems considering the expected generation and consumption, which results in overall cost benefits (Chen et al. 2013). AI can also provide insights on the appropriate strategy for energy storage or energy release to further enhance cost-effectiveness (Liu et al. 2011). As AI technology transforms it will also prioritise the scaling aspect, which will boost the renewable energy projects even more, making them economically viable at all levels. Particularly within microgrids, clean energy resources are rendered economically feasible through AI systems. This metamorphoses the power-generation sector, pushing mankind to harness the immense potential of green energy (Petrakopoulou 2017).
Similarly, it is possible for South Africa to use AI towards incorporating other sources of renewable energy, for example wind and solar energy, into the national energy grid. This will lessen the reliance of the country on coal thermal power plants and encourage energy sustainability (Amansure 2024). Looking at the examples established by Dubai, the UK, and other top nations in the world, South Africa stands to benefit a great deal in the process of improving her energy infrastructure. The implementation of energy management systems that use AI is expected to enhance the country’s energy efficiency, create a sustainable energy system, and build a more adaptive society.
Criminal justice and public safety
In South Africa policing is complicated by a huge deficit in technology, as evidenced by the Khayelitsha Report (2014). Some of the problems highlighted in the report include a lack of policy on issuing all South African Police Service (SAPS) officials with email addresses and the sharing of one email address by senior personnel, which compromises the security of information and leads to lapses in communication (Khayelitsha Report 2014). Despite the measures advanced in many circles, there are still technological shortfalls, which suggest that the police department needs to adhere to minimum basic technological standards. AI refers to machines undertaking certain inherent human functions, such as reasoning and scientific solving of problems, which is a good reason why policing is being enhanced by the use of technology
(European Parliament 2021a). These systems work by studying past occurrences of crime to determine where best to deploy police officers at specific times, using data and algorithms to make probabilistic inferences based on time occupancy patterns (Završnik 2020; Strom 2017).
The level of public trust towards the SAPS has considerably diminished as a result of communities being engulfed by fear. Citing Burger (2011, p. 13), this scenario has arisen from a plethora of issues including (but not limited to) poor budgets, lack of resources, police corruption, insufficient training, and the abuse of civil rights. This is supported by findings published in the media, on social networks and in scholarly works. Embracing technology as part of crime fighting has become the most viable course of action for overcoming the inefficiencies. Tackling crime and corruption will remain impossible unless the South African government takes a bold step and integrates digital technologies in all spheres of policing as soon as possible (Albertus 2019, p. 4).
Furthermore, the Constitutional Court, in AK v Minister of Police [2022] ZACC 14, para 95, addressed the need for police to be vigilant in their readiness to act on behalf of the general public. The Court made it clear that the police must not only fund the activities but fund them with due diligence and within a specified timeframe. It is one thing for the police to make use of existing resources – it is quite another to act reasonably to obtain material, including eye witness accounts, clues, and suspects. Also, forensic examination should be conducted on any materials relevant to the investigation, with due diligence and attention by the police, and refraining from any form of negligence or disregard of duty.
The influence of technology advancement, especially in Facial Recognition Technology (FRT), has greatly helped in solving crimes. As Byrne and Marx (2011, p. 17) state, FRT has replaced conventional approaches to suspect tracking to deliver improved and reliable results in offender management. Nonetheless, there are some worries about FRT, especially its reliability. There are concerns in this regard when it comes to data misreading and data biases (Babuta and Oswald 2019, p. 13). These issues are critical in assessing the ethical implications of AI on policing efficacy, especially for surveillance and tracking use where individuals are targeted. The UN Special Rapporteur (2019, para 12) states that such technologies are likely to further covertly or avowedly discriminatory practices based on race, sex, or ethnicity, as in the case of Chinese Uighurs who are reported to be subjected to facial recognition scanning systems.
While these apprehensions persist, FRT has not ceased to be incorporated into policing structures, most notably
60 | Proceedings of the conference on Public innovation, develoPment and sustainability