Material and human actors coexist in sociomaterial society, an ontologically philosophical sphere, in our new materialistic universe. Philosophically, sociomaterial civilizations think humans and materials are equal. Most materialist companies employ gig economy networks. Examples include Uber, Baedal Minjok, SSG, Coupang, and Market Kully. Although gig economy platform businesses have succeeded, we find it ludicrous that so many human gig workers (HGW) should be subject to a unidirectional order-taking method from their algorithmic bosses, known as AI-driven algorithmic management systems. AAMS typically forces HGW to work or resign without pay when they meet. This one-sided relationship between HGW and AAMS is the result of a dominant mindset that views the company as king and expects its employees to obey its orders to maximize profit. This post disagrees with gig economy sites’ business practices in a new way. The flexible design thinking approach assemblage actor-network theory system (AANTS) should replace the present AAMS. We suggest giving HGW and AAMS a leeway region inside AANTS to settle any difference philosophically using deep learning and ODEs (Ordinary Differential Equations). This paper concludes with our suggested AANTS’ theoretical and practical consequences. Analyzing empirical results requires more research. This requires real-world datasets, which are hard to collect, or synthetic datasets made using statistically significant and robust approaches.