Paper short abstract:

In this modernized world, sexual pleasure is becoming one of the important needs. With gender related laws limits our species exploitation, AI paved a new way to imitate, simulate our sexual needs and redefine us. Here, I attempt to shed light on how AI transforms our sexual life.

Paper long abstract:

What happens when our hypothalamus part of the brain, evolved for eons, suddenly hits the 21st-century world? Imagine an Intelligence that hits our psychological perspective of exploring friends and gossip with friends, match-making or making love intimately. After innovating our technologies to nullify Turing Test, Is not it a new social movement in form of AI? The Anthromophization of Machines/Robots, The Psycho-synchronization of AI paved a new way to live a new sexual life. The sex robots which simulate a human feeling of intimacy is also providing a feeling of biological intimacy, too! The technologies of Sextech, Femtech, Lioness, Realdolls is really proving the pleasure of sex. Is the machine evolving itself to provide the best sexual pleasure? Are these machines help us to establish Healthy Sexual Expression, education, knowledge about social contact and improve our physical relationships? The AI's in social media- does it really enable us to understand our sexuality and sexual desires! Will it be a Cognitive Overload or a Subliminal Overload for both humans and AI? This will make us understand our society and sexual life in a new perspective to our primitive speculations and thoughts.

The movies like "Ex Machina" and Games like Nintendo's "LovePlus" or Quantic Dreams' "Detroit- Became Human" Give us a Visualization of How the world Act like with manly conscious humanoid! Will it become an Experience or a simulation; which I tried to understand through Digital-Techno Ethnographic study.

Paper short abstract:

This project proposes a care robot for an independent elderly. This robot, Sambo, is shape-shifting and provides support to the elderly living alone in their homes. This project also focuses on defining the ethics of different stakeholders involved in creating this robot.

Paper long abstract:

The growing proportion of elderly in society, together with recent advances in robotics, makes robots in eldercare increasingly likely. The author looks critically at how a robot and the elderly could develop a reciprocal relationship of care-giving and care-receiving. This is done by understanding the existing robotics space and gaining insight into their social, cultural, political and ethical implications.

The project's seeds lie in realizing that even the elderly want to be self-reliant and retain their agency. The project doesn't negate that they need care but highlights that mechanisms to make care a reciprocal process are required. Often, care towards elderlies infantilizes them, leading to a loss of dignity in the elderly. They suffer from psychological and physiological pain as soon as they shift towards becoming dependants.

Sambo is a care robot that follows the elderly when they walk, shape-shifts to provide support, and inflates an airbag if the elderly is about to fall to minimize their injuries. Most importantly, Sambo converses with the elderly, plays games, and provides psychological support. Sambo is not just a caregiver but enjoys care in return and demands the same from the elderly. Sambo helps build a reciprocal relationship between the elderly and the robot, uplifting the elderly's self-reliance. The author also throws light on the human-robot ethics through the lens of Sambo.

Paper short abstract:

Cities are vulnerable to heat as the climate changes. AI systems can analyse environmental data and feed generative models; designing cities to reduce heat. This paper will present machine designed urban areas intended to reduce heat, comparing their thermal performance and form to human cities.

Paper long abstract:

Urban areas are particularly vulnerable to climate change. However, current urban planning tools and practices have limited capacity to predict the effects of projected larger-scale temperature changes on existing and planned urban areas with local precision. “Heatmapper” is a mapping application which models and forecasts land surface temperature for urban areas, using a deep learning computer vision model which integrates remote sensing, meteorological, and urban-morphological data to forecast local temperature.

Heatmapper allows users to tune parameters to assess the effects of proposed land use change (e.g parks, buildings, canals etc) on local temperatures during heatwaves. Accordingly, it is also possible to build generative models optimised for specific outputs (e.g. lowest average temperature) which suggest changes to the urban landscape.

Remote sensing data can present an attractive opportunity for training models, but is also fraught with issues of generalisation and reproducibility, as well as the surveillance capitalist logic which underlies the creation of these platforms. A generative model which learns from the best quality remote sensing data will reproduce urban design as it exists in the wealthy countries which provide such data – potentially excluding urban forms from elsewhere. As humans and computers work together - this poses questions over algorithmic and human agency, and the embedding of bias in this human-machine collaboration. This paper will present algorithmically designed cities which utilise Heatmapper, and compare these to real cityscapes to better understand the role machines can play as urban designers.