Examining Technology Accessibility for non-English-speaking, Illiterate and Rural Communities in India

The availability and effectiveness of technology and the Internet are influenced by various factors such as age, education, and urbanization, as these are primary determinants of access and awareness of technological advancements. Proficiency in a language, usually English proficiency, also plays a crucial role in adopting and utilizing technology. Despite growing digitization rates, inequality remains prevalent, primarily based on socioeconomic and sociodemographic status. This term essay delves into the inequalities in accessing technology, including digital literacy, economic status, and language proficiency within India. The practical implementation of technology and connectivity can make a significant difference in the socioeconomic levels of a community, as genuine progress is achieved through inclusive growth. The impact of technology on our lives has been revolutionary. It has improved communication, healthcare, education, economic growth, and agriculture. However, not all have access to these technologies. This essay focuses on technology accessibility and the challenges faced by India's illiterate, rural, and non-English-speaking populations. The unequal distribution of access based on various factors resembles Deleuze's societies of control, where they are indirectly controlled by the technology they cannot access, requiring intervention. For instance, a farmer in rural India might believe that they are freely practicing their agricultural skills. However, the technological advancements inaccessible to them still control the outreach and consumption of their produce.

Technology accessibility is crucial and needs discussion in the context of ethics. Technology ethics revolve around injustice and maximizing the good impacts on the users' lives. So, firstly, it is necessary to provide equal opportunities for all to access and benefit from technology. In parts of rural India, where access to the Internet is still a dream, people find it challenging to access job opportunities, medical services, educational resources, and even their country's political affairs. Ensuring equal access to all opportunities is the initial and fundamental step toward a just society. Promoting social inclusion and reducing social isolation is essential in a populous and diverse country. Thus, technology accessibility can help connect communities regardless of their geographical or cultural boundaries. This allows different communities to interact, collaborate, and exchange knowledge. The arrival of social media platforms such as Facebook, Instagram, and Twitter has enabled people to connect with friends, family, and like-minded individuals across the world who share similar beliefs and interests. Online forums like Reddit and Quora provide users with a platform to share experiences, ask for advice, and seek support. Technology also helps individuals learn about different cultures and communities, making it easier to communicate and collaborate. For example, social media has helped us learn about terms and phrases that might be problematic or insensitive in an unfamiliar community. Equal access to technology promotes a country's economic growth and development, as it is a critical tool for innovation and productivity. Technology can transform industries; for instance, the digitization of payments in India has increased the number of small businesses and profoundly impacted the country's economy. If made accessible to farmers in rural India, technology can help flourish the agricultural sector in the country. Enabling farmers to contribute to economic growth by participating in the digital economy can assist them in independently and directly selling their goods to consumers without intervention and exploitation from the mediators and traders.

As per the 2011 Census of India, around 68.84 % (0.83 billion) of the population resides in rural areas; and India has only 10.6% (129 million) English-speaking population. English is the predominant language used in technology in the current era. However, India's rich cultural and linguistic diversity poses a challenge in adopting technology in the same way as the Western world. While translating information into Indian languages seems like a viable solution in theory, more than 200 languages are spoken across India, making it a difficult task. It is highly improbable that literate and English-speaking developers can make information accessible to people from all linguistic backgrounds in the current decade. Therefore, alternative solutions must be explored, and recent advancements in technology accessibility must be examined. In India, inequalities in accessing technology include geographic area, literacy, digital literacy, economic status, and language proficiency. For decades families around India have been migrating from rural towns to urban cities to access opportunities and services that are usually inaccessible in rural parts of the country. However, this is only a feasible and affordable solution for some. Reducing inequalities starts by spreading these services and technologies across boundaries to rural regions. The anticipated spread of the Internet of Things (IoT) poses significant challenges to technology experts with the task of delivering digital solutions that are simple, secure, and intuitive to operate and that also cost users little to access electronic services and the Internet wholly (Datta et al. 79). More than 103.9 million people in India are older than 60; 56.5% are illiterate or have no access to information and communication technology (79). We cannot look at the factors affecting the inequalities in technology accessibility as independent entities. Instead, we need to find solutions to tackle them as one. For older populations, we must consider literacy, digital literacy, and illnesses affecting cognition capabilities in old age—another thing to acknowledge cultural translations, interpretations, and terminology of the information in new technologies. Every day there is a new slang or meaning for an old word, so researching and evaluating the vocabulary for instructions is crucial. Moreover, how different groups engage with technology must be studied to better cater to specific needs. The content and applications must be adapted to match the user's skill level. Research in this area would result in better techniques for engaging newcomers to the technology and more intuitive interaction techniques for digitally savvy users. On the output side, the primary focus is on the representation of the applications by visual icons and widgets. Such visual tools could augment voice instructions, which users may choose to silence (80). The goal is to let users independently use technology without learning complex skills. In rural Tamil Nadu and other predominantly illiterate communities worldwide, computers and technology are currently only possible with the help of a literate mediator (Plauche et al. 83). Many individuals avoid technology if there are words they cannot read or understand. Literacy increases farmer productivity and earning potential. Literacy is also essential in social potential, such as children's health and nutrition (83). Solutions for technology accessibility must focus on increasing potential similar to that of illiterate individuals without hindering the current scenario. Technology accessibility does not mean simplifying everything; that could lead to vagueness. However, an alternative to investigate is providing choice. UX Designers go through thorough research to understand the needs of different users and design options to switch between or choose from; for example, in today's age, most applications, websites, and services have a button to select the preferred language. Now we explore the complexity of linguistic diversity in India and the challenges it poses for the future of accessibility. Reports show that language gaps and cultural differences play an important role in some population subgroups' underuse of health services (Riddick S41). There is a need to develop standardized evaluation tools for a provider's linguistic skills (Riddick S42). Currently, most technical services provided worldwide predominantly operate using English. Since over 200 languages are spoken across India, IT companies in the West must understand the needs of their Indian users. In April 2017, Google and KPMG released a report, Indian Languages - Defining India's Internet, on the presence and reach of Indian languages online. The key takeaways included that Indic language internet users (234 million) have already surpassed English users (175 million), and this trend will only accelerate as time goes by. According to the Digital Indian Language Report by Reverie Language Technologies, Hindi, Marathi, and Gujarati are the three most used Indian languages online, even though Gujarati is not among the top three Indian languages by native speakers (Arvind Pani). Thus, making technology accessible to such a large market will deeply benefit the tech industry.

In a significant push forward, the Government of India mandated digital Indic language support in 22 languages for all mobile devices in India, a push decisively in favor of their increased digital presence. In addition, the Government of India has been pushing for more government services to be available online. As internet penetration increases, the Internet increasingly becomes both an outreach platform for and a facilitator of government services (Arvind Pani). The Government of India unveiled UMANG (Unified Mobile Application For New-Age Governance) app in November 2017, and it came with support for 12 Indian languages. UMANG's nature as an all-in-one government app that lets citizens find and access other government services means that UMANG's language support will facilitate easier access to government services in general (Arvind Pani). With its mission of bringing digital payments to the masses, BHIM developed keeping accessibility in mind. It was released with support for multiple Indian languages, ensuring the average Indian citizen would have as much access to digital payments as their English-speaking, upper-middle-class fellow countryman (Arvind Pani). All these recent developments concentrated on the linguistic diversity of the Indian user market and catered to their particular needs to digitize the country. However, these solutions are not accessible to all and require further advancements. Simply translating into around 20 languages does not solve the challenge, so exploring new technologies, such as Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and Speech-driven User Interface (UI), might be the next step.

Indians coming online for the first time may be more comfortable searching by voice than typing since Indic language typing would be entirely new. Voice, on the other hand, is not. According to Google's data, 28 percent of Google searches are done in India by voice queries (Arvind Pani). Using voice or speech can help to make information and technology more accessible for non-English-speaking, illiterate, and rural users through limited vocabulary. Traditional speech technologies and user interface design, developed for (and by) the literate in resource-rich countries, are poorly fit for users in developing regions (Plauche et al. 83). Speech-driven user interfaces (UI) are cheaper than display-based UI solutions and more accessible than text-based UI solutions. Many applications for rural Indian information technology (IT) that provide information on health, weather, employment, news, and agriculture could enhance the social and economic development of the economically disadvantaged in rural regions and utilize a limited-vocabulary speech-driven interface (84). Speech-driven UI solutions aim to increase access for users in developing regions, but they face challenges of multilingualism, dialectal and cultural diversity, and prohibitive costs. The availability of linguistic resources, such as training data and pronunciation dictionaries, arguably the most costly part of development, are taken for granted by developers with English-speaking users in mind, for example. Although, illiteracy usually describes an individual's competency in reading and writing tasks. A functional illiterate is an individual who may have had some exposure to education but whose low competency at these tasks prevents the individual from wholly participating in society (84). However, designers and developers must abandon these theories to produce the most accessible solution. One solution is a multimodal interface that requires no training and provides users with various visual and audio cues and input options, allowing each user the flexibility to interact with the application to the best of their ability and the system's ability. TamilMarket, an SDS that runs on a laptop to which participants speak using a custom phone mic, primarily operates with the Tamil words for "yes" (aamaam) and "no" (illai), which are likely to retain their meaning and function across different dialects. Explicit prompts for input options and a redundant structure ensure that users have access to all available information, albeit not in the most direct way, even with misrecognized or missing inputs. In this way, TamilMarket can accommodate first-time users and users unfamiliar with technology without needing a separate training session (85). Integrating the collection of linguistic samples into the SDS can help as recording speech does not favor literate users over illiterate users and provides the best match of training and input data, resulting in robust ASR performance despite limited linguistic data (90). The technique used by TamilMarket can benefit other technologies around rural India.

Machine Learning can help power more accurate, precise translation, which is essential for localizing content at scale in linguistically diverse and non-English-speaking communities of India. Furthermore, ML can assist with remote-simultaneous interpretation, a real-time translation technique that allows individuals to hear their preferred languages being spoken almost simultaneously with the originating speaker in an IoT device; for example, calling hospitals to set up appointments can be more accessible. Another solution to making textual information more accessible is using visuals. Artificial Intelligence (AI) can help applications or services translate textual instructions into images to reach more users. For example, Midjourney is a generative artificial intelligence program capable of text-to-image translations, and its integration into IoT or mobile applications can benefit diverse Indian communities. Image generation is progressively examined in today's artificial intelligence globe. The conversion of text to images is an exciting application of the Generative Adversarial Network (GAN). GAN enables feature extraction from the sentence and converts it into an image. Though GAN has many valuable applications, it has a significant disadvantage in that it takes a large number of data for training and processing resources. Even for simple tasks, GANs require vast data (Sawant et al. 1).

The deaf community in the world uses gesture-based language, generally known as sign language. Every country has a different sign language; for instance, the USA has American Sign Language (ASL), and the UK has British Sign Language (BSL). The deaf community in Pakistan uses Pakistan Sign Language (PSL), which like other natural languages, has a vocabulary, sentence structure, and word order (Khan et al. 748). Most English language sentences use subject, verb, and object (S+V+O) word order in sentence formation. In a survey, over 80% of the sentences collected from the deaf community in Pakistan followed the (S+O+V) word order. Therefore, (S+O+V) is the default word order for PSL sentences (752). All Indo-Iranian languages (examples: Bengali, Gujarati, Hindi, Marathi) and nearly all other Tibeto-Burman languages (examples: Kannada, Malayalam, Tamil, Telugu) also have (S+O+V) structures. So, a rule-based machine translation model proposed to translate English text into PSL that takes an English sentence as input and translates it into PSL can also aid the non-English-speaking communities in India.

Coming from a rural community in India, I have witnessed the inaccessibility my non-English-speaking parents and relatives face in the current technological world. I have found them to reply on visuals every time they're in an alien environment and avoid looking at interfaces filled with English texts. Whenever I mention this linguistic difference with people in urban cities, I am not surprised to learn that most do not look at it as an issue at all. I am always met with the same reply, "Just add translations!" My first language or mother tongue, Haryanvi, does not even exist on Google Translate. So, it is challenging for illiterate and non-English-speaking individuals from rural India to transform into "users" of technology. Through this essay, I attempted to explore methods to make information and technology more accessible to these communities so they do not feel alien outside the boundaries of their towns. I have recently been developing Augmented Reality assistance to help non-English-speaking users navigate through indoor and outdoor spaces. It uses speech recognition to trigger a 3D animation of a person walking in front of the user and guiding them to the desired destination. I have found that it is relatively more accessible for people to remember the names of destinations or places than reading complex textual instructions. This essay examined the current state of accessibility in technology and how it caters to non-English-speaking, illiterate, and rural communities in India. Furthermore, various technologies were explored and studied to help relate to the Indian context. In conclusion, Artificial Intelligence and Natural Language Processing integrated with speech-driven UI can be a potent tool for technology accessibility in the coming years.

Works Cited
  • Khan, N.S., et al. “A Novel Natural Language Processing (NLP)–Based Machine Translation Model for English to Pakistan Sign Language Translation”. Cogn Comput 12, 748–765 (2020)
  • Datta, Arijit, et al. “Bridging the digital divide: Challenges in opening the digital world to the elderly, poor, and digitally illiterate.” IEEE Consumer Electronics Magazine 8.1 (2018): 78-81.
  • Plauche, Madelaine, et al. “Speech recognition for illiterate access to information and technology.” 2006 International conference on information and communication technologies and development. IEEE, 2006.
  • Riddick, Sherry. “Improving access for limited English-speaking consumers: a review of strategies in health care settings.” Journal of Health Care for the Poor and Underserved 9.5 (1998): S40-S61.
  • Arvind Pani. “The Indian Internet’s Second Big Turning Point Will Be Language Tech.” Your Story, https://yourstory.com/2017/12/2017-language-tech-indian-internets-turning-point. 2017.
  • Sawant, Ronit, et al. “Text to Image Generation using GAN.” Proceedings of the International Conference on IoT Based Control Networks & Intelligent Systems - ICICNIS 2021.