10 :: ? started a journey of finding out how creativity can be enhanced by AI. Among them, Matthew Yee- King, a musician who is employing evolutionary and genetic algorithm to work on sound synthesis. Meanwhile, Mario Klingemann, a code artist at the Google Cultural Institute, is applying deep learning to large image datasets for creating huge, stunning digital art. More details in this regard can be found from ArtFab at Carnegie Mellon University (Carnegie Mellon University, 2018). Mid-Term Cases: Human and AI-Collaborated Digital Art Creation Robots are marching towards us and the user friendly interface will become a crucial element for facilitating the interaction between human and robots (Xing and Marwala, 2018). Accordingly, the experience of taking the audience and artist relationship into account, and forming a kind of new job, such as practical aesthetics, is quickly blurring the conventional hard lines among algorithm programmer, engineering designer, and the artist. Other similar, emerging new job titles include Chief Experience Officer, Virtual Reality Editor, Mixed-Reality Designer, Bot Developer, Hologram Retail Display Designer, and many more (Kapko, 2017). Long-Term Cases: Art Decentralized Autonomous Organization (ArtDAO) Nelson Mandela once said (BrainyQuote.com, n.d.): “Money won’t create success, the freedom to make it will.” However, one of the main and long-standing disadvantages of the Internet is its hidden “artist penalty”, that is, creators find it hard to create and distribute digital content freely over the Internet while keeping themselves fairly remunerated. The ownership and copyright issue has thus become the biggest problem of digital art (Bentkowska-Kafel et al., 2005). With the progress of AI and some key infrastructural technologies, say, block chain, this problem is more likely to be resolved after the appearance of Art Decentralized Autonomous Organization (ArtDAO), a preliminary version of Skynet in the market (Marwala and Hurwitz, 2017). In its simplest form, the ArtDAO works as follows (McConaghy and Holtzman, 2015): (1) Start and prepare yourself; (2) Generate new images by running an AI art engine with the help of genetic programming or deep learning; (3) Announce the attribution via block chain-bolstered platform, e.g., Ascribe; (4) Sell different editions on the marketplace, either centralised (e.g., Getty), or decentralised (e.g., OpenBazaar); (5) Claim remuneration from ArtDAO via cryptocurrency; (6) Check the termination criteria (e.g., whether you are satisfied with your income). If the stopping conditions are not yet met, then go to Step (7), that is, repeat the procedure and create more digital arts. Outlook Very few features of humanity are more charming than creativity; and rarely any other fields are more dynamic now than AI. The current usefulness of AI does not necessarily dwarf our human’s creativity; on the contrary, the research and development of AI is largely spurred by our own internal creativity. Take interior search algorithm (Gandomi, 2014). The underlying inspiration sources were actually from the latest innovation in fine art (e.g., mirror work) and interior design process. Other examples also include music inspired algorithms, teaching- learning-based optimisation, and so on (Xing and Gao, 2014b). A notable case goes to military operations inspired AI algorithms (Sun et al., 2016; Yang et al., 2018), which in turn can help us with modelling militarised conflict (Marwala and Lagazio, 2011). A bit outside AI realm, it was reported that the Tibetan knot (human artist’s creation) has inspired German chemist Kekulé to finally discover the structure of benzene (Olteţeanu, 2016). The domain of AI is rapidly evolving: narrow AI is good at pre-determined tasks; with AGI, we are targeting solving any problem in general; while for conscious AI, a true or self-aware version of AI is envisioned. Poems were once regarded as a unique product of human creativity, involving multiple dimensions of emotions and sentiments. However, during a recent Chinese national poem contest, an AI-powered robot beat three other rivals and won the champion prize (Lan, 2018). Does this mean that AI is able to “think”? Is this dangerous or not? Interested readers can use (Lawless et al., 2017) as a reference for finding out more own interpretations. :: Professor Tshilidzi Marwala Vice-Chancellor & Principal University of Johannesburg