Category Archives: AI

What does it mean to be human?

With the surge of interest and investment into AI, the question at the forefront of my mind is ‘What does it mean to be human?’ The apparent obsession with AI is to replicate human intelligence on all levels, but the problem I have with this is that I don’t think we fully understand what it means to be human. I think it is impossible to reproduce human ‘intelligence’ without first appreciating the complexities of the human brain. Hawkins (2004) argues that the primary reason we have been unable to successfully build a machine that thinks exactly like a human, is our lack of knowledge about the complex functioning of cerebral activity, and how the human brain is able to process information without thinking.

This is the reason why the work of Hiroshi Ishiguro, the creator of both Erica and Geminoid, interests me so much. The motivation for Ishiguro to create android robots is to better understand humans, in order to build better robots, which can in turn help humans. I met Erica in 2016 and the experience made me realise that we are in fact perhaps pursing goals of human replication that are unnecessary. Besides, which model of human should be used as the blueprint for androids and humanoid robots? Don’t get me wrong, I am fascinated with Ishiguro’s creation of Erica.

My current research focuses on speech dialogue systems and human computer interaction (HCI) for language learning, which I intend to develop so it can be mapped onto an anthropomorphic robot for the same purposes. Research demonstrates, that one of the specific reasons the use of non-human interactive agents are successful in language learning is because they disinhibit learners and therefore promote interaction, especially amongst those with special educational needs.

The attraction is of humanoid robots and androids for me therefore, is not necessary how representative they are of humans, but more about the affordances of the non-human aspects they have, such as being judgemental. In my opinion, we need more Erica’s in the world.

What does 2020 mean for Ed Tech?

A new year AND a new decade, so what does 2020 mean for Ed Tech? Twenty years ago we were getting to grips with communicating via email. Ten years ago iPhones had already been around for three years, but their price bracket pitched them out of reach for the majority of mobile phone users. So here we are in 2020 with driverless car technology being widely tried and tested, and with China witnessing the birth of the third gene-edited baby. So where does this leave language learning and tech, and what is in store for the near future?

Where we are now

Apps, apps, apps… With the 2019 gaming community reaching a population of 2.5 billion globally (statista.com), it is no surprise that apps are an attractive option for learning English. The default options tend to be Babel, Duolingo and Memrise, but there are a plethora of options to choose from. Some recent fun apps I have experimented with are ESLA for pronunciation, TALK for speaking and listening, and EF Hello.

In the classroom however, the digital landscape can be quite different. Low resource contexts and reluctance from teaching professionals to incorporate tech into the learning environment can mean that opportunities for learners to connect with others and seek information are not available. Even is some of the most highly penetrated tech societies 19th century rote based learning and high stakes testing approaches are favoured.

Predictions for the future

Does educational technology have all the answers we need to improve the language output of ESL learners globally? No, probably not. However, society has been so dramatically altered by the impact of technology in almost every facet or our lives, it would be rather odd I feel, to reject it in teaching and learning environments.

In higher education the main concern is data privacy and ethics with exposure to digital areas such as the cloud. Yet, chatbots are starting to become integrated to support students asking university related FAQ’s. Both Differ and Hubert chatbots are being researched for their potential to improve qualitative student interaction and feedback.

Kat’s predictions

In all honesty I think it is a tough call to gauge where we will be with Ed Tech during the next ten years. Data privacy is a considerable issue when incorporating elements of AI into learning fields. This is not an issue with VR and AR and therefore underpins its relevant proliferation in teaching and learning. I feel that VR and AR will continue to mature and provide a more full-bodied learning experience when using VLEs. This may however be a slightly more complex paradigm than some may be able or prepared to employ.

I still firmly believe that reflective practice is a solid foundation for learners using recorded audio or visual content of their language production. So while this doesn’t mean the introduction of a big pioneering tech tool, it highlights its relevance as a reliable learning tool. In the same way, I continue to use Whatsapp, WeChat and Line to share learning content with learners and encourage them to interact with each other, and other learning communities.

AI: a new currency or the next industrial revolution?

A question that has been on my lips recently is whether AI is set to be the next industrial revolution, or a new currency of the future.

AI Past

The industrial revolution as its name denotes, revolutionised modern industry and manufacturing as we know it today. When the internet emerged in the late 1980s it seemed unimaginable that less than 30 years later, wireless connections and digital devices would have such a pervasive presence in society. New inventions come and go, and technological innovations are created whether they are successful or not, but in most cases they are shaped by the demands of people.

The origins of AI date back to Turing’s computational machine more commonly known as the Turning machine, built in 1935, however the term was coined later in 1955 by McCarthy who defined it as “the science and engineering of making intelligent machines, especially intelligent computer programmes” (ibid 2001:02), in other words trying to understand human intelligence by using computers.

AI Present

During the last 80 years, advances in AI technology have reached astounding levels. It has clearly had a prolific impact on society, to the extent that it has been transformed into a tool in all aspects of life; from banking and email pop ups, to ‘personalised’ selected products, and Siri and Alexa the intelligent personal assistants, and chatbots.

AI Future

Both academic and business investigation and reporting in the field of AI, consider it to be one of the biggest influencers for the future of the market and society. Predicted revenues from AI are unprecedented, resulting in extensive funding and investment from private companies and governments, which highlights the significance of AI in society. China has recently announced they are building a $2.1 billion industrial park for AI research. The past year has witnessed an increasing amount of nations realising the importance of AI in shaping the economics of the future, some even consider it a currency. Bitcoins stand aside, AI is the new currency..