Prosthetics and AI

Prosthetics and AI

The human body is a fascinating machine. Quite complex and intricate. Next to the human heart and mind, the four limbs (i.e. arms and legs) are an intrinsic part of how we define ourselves in life. But not everyone is fortunate to have a healthy pair of limbs. Due to war, disease, accidents or genetic anomalies, not all human beings are blessed with a working pair of limbs. Most lead on to have sad and unproductive lives. Some even resort to begging and stealing to make ends meet. It’s at this juncture that artificially powered limbs become critical. While they’re yet to be the perfect replacement to natural limbs, AI enabled limbs are catching up and exhibit interesting technologies that can perform nearly if not all the functions that a natural limb can. But what and how do these artificial appendages work? Let’s find out

Human hands and legs, while stationary when not being used, require a complex system of signals emanating from the brain to perform any function. Everything from walking to writing to swimming to painting, almost anything that requires use of the limbs, requires a variety of signals from the brain to perform the intended function. Artificial limbs are built on a similar principle. When a person, who’s lost the usage of his/her natural arms/legs or both, is fitted with artificial appendages, the latter takes cue from the nerves of the human user to perform any function. The appendage is fitted with a variety of sensors to replicate what its human user has in mind for it. 

Using a vast amount of data such as the pressure, angle, shape, contour and fluidity of natural human limb movement, the AI enabled appendage can mimic its siginificant better’s movement precisely. The degree to which it can perform such a function depends on the level of sensitivity the sensor encompasses. To ensure optimal usage under a variety of conditions, an AI enabled appendage is loaded with a variety of microprocessors that essentially perform the role of a human hand or limb. One such company that has made giant strides in this field is Ottobock. Named after the 20th century German prosthetist Otto Bock who made some of the world’s earliest prosthetics for soldiers injured in the 1st World War, this german based company has made a commendable prosthetic hand; BeBionic

BeBionic is a hand that has 14 selectable grip patterns along with an additional auto grip feature. Featuring powerful microprocessors and individual motors for each finger, this contraption can handle loads of upto 45 kgs. It also has soft finger pads along with proportional speed control that enables it to allow the user to grip a variety of surfaces with ease and confidence. 

Another prosthetic aid that has gained international recognition is the one that was used by former Paralympic gold medallist Oscar Pistorius. The ‘Cheetah Xtreme’ features elements such as ‘Active tibial progression’, a feature that mimics the sprint and stop power of Olympic level able bodied athletes; ‘Proportional Response’ that takes into consideration the user’s weight and the impact of the heel with the surface as well as a ‘Waterproof internal structure’ that doesn’t allow water to seep in

Though prosthetics and AI still have a long way to go before they’re able to bridge the gap between paralympic and olympic level events, the giant strides they’ve made, courtesy the above two wonders, is commendable. 

Combating Hate speech and fake news with Artificial Intelligence

Combating Hate speech and fake news with Artificial Intelligence

While Information Technology (IT) has made access to information and methods of communication fast, reliable and convenient, it has also led to developments of the sinister kind; the emergence of hate speech and fake news. With about 50% of the world connected to each other by the World Wide Web (WWW) as per an internet penetration rate analysis, emergence of Chinese budge oriented smartphone companies capturing more than 50% of the market share and electricity becoming accessible to many remote areas, censoring the aforementioned maladies is a major challenge.


It is not surprising that social media giants such as Facebook and Twitter had to close down more than 1.5 billion and 70 million accounts respectively to ensure that fake news and hate speech did not lead to radicalisation of people in different parts of the world. But how do these companies manage this humongous task? The answer lies in incorporating Artificial Intelligence (AI) and Human Intelligence (HI) to detect anomalies 


One way that social media entities detect fake news and hate speech is by asking users on their platforms to report abuse or flag comments that are ‘inappropriate’ or ‘horrifying’. Once the user flags a link, video or content, its upto the social media entity to detect traces of maleficent behavior. Facebook has taken help of an AI system called Rosetta to understand the authenticity of a news, photo or content that’s been uploaded on the system. 


What Rosetta does is in plain english is this; it scans the word, picture, language, font, date of the post amongst other variables and tries to see if the information being presented is genuine or not. The role of human annotators is without a doubt the most difficult and dangerous. Given that the AI system is not fully adept at understanding innuendoes, references, slights and the contexts in which the content was posted, its upto the human moderators to guide the AI system in discovering fake news and hate speech which are interspersed with murder, pornography and rape


This methodology has already been adopted or looked up by entities dealing with people’s opinions, comments and perspectives. While some content moderators have hailed the confluence of AI and HI to combat fake news and hate speech, some feel that a lot more needs to be done. Given that the lingua franca between people across the world is majorly in English with a lot of anglicisation, detecting malicious content is a superhuman endeavor that cannot be fully curtailed because that would mean stomping down on people’s right to expression. Navigating the tightrope between data privacy and content moderation is another thing data analysts highlight upon. 


However, the fight to ensure that a world where love not war, kindness not anger and bonds instead of bullets exist is on. 

Big data and Disaster management

Big data and Disaster management

Disasters, both natural and man-made, have afflicted a great amount of damage to living and non-living beings since time immemorial. While ancient methods of disaster mitigation such as developing barriers, getting alerted via abrupt bird and animal movements and sounds and archaic methods of relaying data did prove beneficial, they weren’t foolproof. Owing to lack of close integration, many a times, these methods failed to get the intended result. The advent of the Information Technology (IT) age led to interesting developments in the field of disaster management. For not only did IT help us in formulating disaster mitigation strategies years, if not decades, in advance, they also led to a lot of lives and property being saved in the process. But how does IT help avert disasters? What sort of integration does it follow? Let’s dig in.

The most important element to identifying disasters is to create maps. This depends on the image resolution capabilities of the satellite in question. The higher the resolution capacity, the more intricate the picture can be. And this is crucial in identifying a disaster hotspot not just in the event of a disaster taking place but also to map areas that may face disasters in the near future. Using satellite imagery to build a database of evolving landscapes is crucial in this regard. Using climatology and terrestrial maps over a period of 2-3 decades can help in this regard. In this respect, tying up with meteorological and disaster management departments is the best way forward. 

While satellite imagery can help us in getting prepared for disasters in advance, what about ground mobilisation in the event that disaster does strike? As it happened during the 2015 Chennai Floods and during 2018 Hurricane Irma in USA, rescue efforts undertaken using geo-tagging and sharing live location of people stuck in danger zones led to a lot of lives being saved. Not only did this help in precise deployment of rescue forces, it also led to identification of vulnerable areas that were and would face the most risk if such a disaster were to strike again. The use of the #hashtag proved to be a blessing here. Using this tool, people were able to communicate via Twitter and Facebook and get help. 

Now, if we combine the historical record of a place experiencing disasters with the number of requests from people in an area affected by that disaster, this would yield a treasure trove of data. Building upon the same, governments and city planners can build better embankments in case of flooding or structurally sound buildings in case of earthquakes. The 2015 Chennai floods, one of the worst natural disasters in India, witnessed a surge in social media campaigning to ensure that the worst affected areas received help as soon as possible. Thanks to reliable data from satellite monitoring, residents of many US states vulnerable to the storm were able to evacuate in time and get to safe zones. 

Such a technology can be implemented even in areas struck by human made disasters. Election monitoring firm Ushahidi is one such contender. The Nairobi based startup made an interesting application that could track and report incidences of real time violence in conflict ridden nations. Created by concerned bloggers and software developers in the backdrop of the 2007 Presidential elections in Kenya, it tracked and mapped the post-election violence. The methodology they adopted to monitor the same was not only effective but also low cost. 

The possibilities that big data holds to combat disaster are nearly limitless. With advances in communication technology and e-literacy, managing disasters will become a manageable if not avoidable venture.

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