Easy mini ramp tricks full#
Easy mini ramp tricks series#

Easy mini ramp tricks full#

Can YouTube justify, in detail, why my welcoming page is full of skateboarding and jazz videos? More specifically, I would like to know why the top video displayed this morning is вЂњ10 easy mini ramp tricks for beginnersвЂќ. To put it simple: everybody has the right to understand how its personal data is collected and processed.ДЄnd that is a big challenge for tech companies. The principle of transparency requires that any information and communication relating to the processing of those personal data be easily accessible and easy to understand, and that clear and plain language be used.вЂќ ( Principles of Data Processing, Recital 39) It should be transparent to natural persons that personal data concerning them are collected, used, consulted or otherwise processed and to what extent the personal data are or will be processed. Among all the principles stated in this document, I will focus on the processing part: вЂњ Any processing of personal data should be lawful and fair. With the implementation of the General Data Protection Regulation (GDPR) in the European Union in 2018, the regulation regarding the collection and the processing of personal data took a step forward. The problem is that fake news and conspiracy theories content perform very well with regards to ad revenueвЂ¦вЂќ confessed Guillaume Chaslot, former researcher at YouTube. But they probably donвЂ™t know that YouTubeвЂ™s only KPI is the user watching time. вЂњ Parents let their children watch YouTube without surveillance. Considering AI as Oracle can be dangerous because the algorithm could be wrong, biased, or have hidden intentions. Some Millennials have grown accustomed to accepting AIвЂ™s decisions without looking for an explanation. Second, there is a rising security issue.First, the user has a right to know how his personal data is being used and how the algorithm is trying to influence him (in a good or a bad way).Understanding the choices made by an algorithm is critical for two main reasons: Indeed, algorithms are very often perceived as вЂњblack boxesвЂќ, which produces fear in peopleвЂ™s minds.

The role algorithms have taken in our daily lives brings up an ethical question: can we let algorithm take decisions that we cannot explain?Дuring the Interpretable AI workshop that took place in 2017, Uber AI researcher Jason Yosinkski stated that вЂњ in order for Machine Learning models to be accepted by society, weвЂ™re going to need to know why theyвЂ™re making the decisions theyвЂ™re making. Thanks to todayвЂ™s technical improvements (see the three Vs mentioned above), we can let models be as big and complex as required, permitting algorithms to reach very high precision and efficiency, and thus beat humans. AI beats humans in Games ( Chess in 1997, Jeopardy! in 2011, Go in 2016, StarCraft II in 2019), in Face Recognition ( DeepFace by Facebook in 2014), in Speech Recognition ( Microsoft in 2016), in Machine Learning Coding ( GoogleвЂ™s AutoML and MicrosoftвЂ™s DeepCoder), in Disease Detection ( cancer, pneumonia, eye condition), etc. In a sense, this shift is logical: algorithms have reached such a high level of accuracy and computational power that they surpass humans. However, today algorithms take a myriad of decisions without consulting humans: they have become the decision makers, and humans have been pushed into an artefact shaped by technology. Before, humans were the only decision makers and AI was simply a tool (among others). Over time, the roles of humans and AI have greatly evolved. AI takes advantage of data to make decisions as ordinary as the price of an Uber ride to ones as serious as court sentences. Today, we are right in those three Vs and if you combine Big Data with Applied Mathematics you will get Artificial Intelligence. It is the classical way to define Big Data.

You may have heard of the three Vs of Big Data: Velocity (megabyte to zettabyte), Volume (data broke into batches to streaming data) and Variety (structured & unstructured data). We generate data incessantly, and with the recent improvement of storage capacity and computational power, companies and organisations have jumped on the bandwagon of Big Data.

Easy mini ramp tricks series#

AI seems to know us better than we do, with applications ranging from predicting the next series we are going to binge-watch to the next person we are going to date. The impact of AI on our daily lives is becoming increasingly prominent.