Depending on your framing, the coming age of Artificial Intelligence is either the panacea to all the worlds drudgery or heralds the arrival of our robot overloads and ultimate annihilation.
The truth is clearly somewhere in between, and depends a lot on a careful definition of terms, but either way the arrival of Artificial Intelligence and it’s subordinate cousins Machine & Deep Learning, presents a seismic shift and one which demands our immediate and focused attention.
Artificial Intelligence is here and it’s already doing interesting things, from influencing your Facebook feed to influencing US elections, from predicting your text messages to predicting where extreme weather events will hit, from recognising your voice to recognising endangered tigers.
And that’s just single purpose AI, stuff gets real when we begin to join a few of these ‘intelligences’ together, and Artificial General Intelligence emerges. AGI is still the realm if sci-fi, but for how long and what are the implications?
For the next Greenhouses evening we’ve approached a range of academics and thought-leaders to help us explore this fascinating topic, and help guide us as we decide how we can shape Artificial Intelligence and Machine Learning in to Planet Saving Technologies. More here:http://www.katinamichael.com/seminars/2017/9/26/artificial-intelligence-and-machine-learningas-emerging-technologies-in-social-and-environmental-impact and here: http://greenhouse.org.au/#event-2017-september
Take control of your SAP testing with UiPath Test Suite
Artificial Intelligence & Machine Learning. Is it Planet Saving Tech?
1. AI, Machine Learning, Big Data:
Social and Environmental Impact
Katina Michael
University of Wollongong
katinamichael.com/seminars
September 26, 2017
UTS Energy Lab
2. Basic Definitions
• Artificial Intelligence: a branch of computer science dealing with the simulation of intelligent
behavior in computers. 2 :the capability of a machine to imitate intelligent human behavior.
• Machine Learning: is an application of artificial intelligence (AI) that provides systems the
ability to automatically learn and improve from experience without being explicitly
programmed. Machine learning focuses on the development of computer programs that can
access data and use it learn for themselves.
• Big Data: extremely large data sets that may be analysed computationally to reveal patterns,
trends, and associations, especially relating to human behaviour and interactions.
• Crowdsourcing: the practice of obtaining information or input into a task or project by
enlisting the services of a large number of people, either paid or unpaid, typically via the
Internet.
• Open Data Institute: (ODI) equip, connect and inspire people around the world to innovate
with data.
• Planetary skin: Institute (PSI) is a global non-profit research and development organization
that aims to improve the lives of millions of people around the world.
• Collective Awareness: Platforms for Sustainability and Social Innovation (CAPS) initiative
pioneers new models to create awareness of emerging sustainability challenges and of the
role that each and every one of us can play to ease them through collective action.
3. Mega Cities = Mega Problems
Toward Sustainable Development
• Environmental Stresses
– Air pollution
– Traffic management
– Climate change
• Infrastructure
– Energy
– Water
– Transportation
– Health care
• Mobility/ migration
– Economic development
– Food supplies
• Power consumption
– Cont. to build out
infrastructure and use
them more efficiently
– Proactively manage
demand
• Governance/
coordination
• Financing
• Public-private
partnerships (PPP)
• Natural vs human-made
disasters
14. The Open Data Movement
• Internet of Everything
• Nothing should be private
• Look at the great things big data will herald
• The end of starving children in Africa
• The end of criminal activity by underground
networks
• No more corruption, only transparency
• Nowhere to hide
• Sensors everywhere
17. The Collective Awareness Movement
• Equitable access to energy
• Sharing energy toward sustainability
• Smart grids, smart homes, smart meters, smart
cars, smart phones, smart people
– What’s wrong with this model?
• I know who you are, where you live, what
condition you are in because of the energy you
draw
• If you have something your neighbour does not,
why not share it? Redistribution is great!
26. Source: Committee on Radio Frequency Identification Technologies, Computer Science
and Telecommunications Board, Division on Engineering and Physical Sciences, National
Research Council (2004), Radio Frequency Identification Technologies:: A Workshop
Summary, p. 28, footnote 18.
Stick a chip in every person, of course
Planetary Skin Institute will research, develop and prototype an approach to provide near-to-real-time global monitoring of environmental conditions and changes. This will deliver the required decision support capabilities to manage global resources and risks.