OpenCog is an open source AGI project. But it is is also incredibly complex and IMHO not a good idea (I have not fully read his theories). You can learn the essential ideas behind OpenCog from the co-founder Ben Goertzel site as well.
Or, you can participate in the philosophical discussion regarding AGI. For strictly AGI, decision theory, logic, and math material (they are all related), you can look up stuff from http://yudkowsky.net/ or https://arbital.com/. But, in some sense, every branch of philosophical inquiry can be tied back to AGI and consciousness (ethics, metaphysics, etc.), so if it fancies you it depends on how you'd like to tackle it.
You could also study the psychology end of things. The following papers and related ideas are quite important in the field of study of consciousness and cognition (but keep in mind this is pretty much a random list, the literature is massive!):
Recently, (in mathematical time), progress in category theory shows promise of being a unified framework of much of the existing math. I know next to nothing about it, but the people that do are applying to many new fields of study (including AI, apparently). Category theory requires a lot of background mathematical knowledge before its vocabulary begins to make sense, though, so beware. You can read about it on the nCatLab and occasionally on John Baez's blog: Azimuth
Of course, "regular" techniques in Machine Learning such as neural networks, reinforcement learning, statistical methods, and others are very powerful as well, but due to certain regards in their construction, they are generally understood as only being capable of being "narrow AI" in the sense that they can only complete a single task very well, but perhaps you can find some research that changes this?