Weather wars, authoritarian surveillance, social control, and more are "Future Shocks" that could fundamentally destabilize the world as we know it, according to the WEF. The World Economic Forum (WEF) is currently underway in Davos, Switzerland, but a week before the event, the WEF Global Risks Report 2019 was published identifying weather manipulation tools, social control through biometric surveillance, AI "woebots" that can feed on human emotions, and more as "Future Shocks" that could forever alter the course of human history. "Authoritarianism is easier in a world of total visibility and traceability" The WEF report for 2019 lists 10 "Future Shocks," which are not predictions, but rather "food for thought and action" about current technologies and trends that have the potential to shake up society, for good or ill, in the very near future. Since we at The Sociable like to focus on the technological side of things, especially as how it relates to social impact, let's take a closer look at the Future Shocks that pertain more to technology. "Weather manipulation tools-- such as cloud seeding to induce or suppress rain--are not new" Make no mistake, weather manipulation tools do exist, yet not a single government or group has claimed responsibility for using this technology as a weapon.

Rearranging objects on a tabletop surface by means of nonprehensile manipulation is a task which requires skillful interaction with the physical world. Usually, this is achieved by precisely modeling physical properties of the objects, robot, and the environment for explicit planning. In contrast, as explicitly modeling the physical environment is not always feasible and involves various uncertainties, we learn a nonprehensile rearrangement strategy with deep reinforcement learning based on only visual feedback. For this, we model the task with rewards and train a deep Q-network. Our potential field-based heuristic exploration strategy reduces the amount of collisions which lead to suboptimal outcomes and we actively balance the training set to avoid bias towards poor examples. Our training process leads to quicker learning and better performance on the task as compared to uniform exploration and standard experience replay. We demonstrate empirical evidence from simulation that our method leads to a success rate of 85%, show that our system can cope with sudden changes of the environment, and compare our performance with human level performance.

Data is the new language today. Data leads to insights, and insights help organizations to make actionable business decisions. However, sourcing the data and preparing it for the analysis is one of the tedious tasks organizations face these days. Analysts devote a lot of time in searching and gathering the right data. According to a research firm, analysts spend around 60 to 80 percent of their time on data preparation instead of analysis.